Test Bank For Basic Statistics For Business And Economics 7th Edition By Douglas A. Lind, William G by StudyGuide

Test Bank For Basic Statistics For Business And Economics 7th Edition By Douglas A. Lind, William G. Marchal, Samuel A. Wathen, Carol Ann Waite, Kevin Murphy Chapter 1-17

Chapter 1 Student name:__________ 1) The general process of gathering, organizing, summarizing, analyzing, and interpreting data

is called: A) Statistics. B) Descriptive statistics. C) Inferential statistics. D) Levels of measurement.

2) The general process of analyzing, and interpreting data to assist in making more effective

decisions is called: A) Statistics. B) Descriptive statistics. C) Inferential statistics. D) Levels of measurement.

3) The general process of gathering, organizing, presenting, analyzing, and interpreting data to

assist in making more effective decisions is called: A) Statistics. B) Descriptive statistics. C) Inferential statistics. D) Levels of measurement.

4) The general process of organizing, summarizing, and presenting data in an informative way

is called: A) Statistics. B) Descriptive statistics. C) Inferential statistics. D) Levels of measurement.

5) (i) The general process of gathering, organizing, presenting, analyzing, and interpreting data

to assist in making more effective decisions is called: (ii) The general process of analyzing, and interpreting data to assist in making more effective decisions is called: (iii) The entire set of individuals or objects of interest or the measurements obtained from all individuals or objects of interest is called: A) (i) statistics, (ii) descriptive statistics, and (iii) a population. B) (i) descriptive statistics, (ii) inferential statistics, and (iii) a sample. C) (i) inferential statistics, (ii) descriptive statistics, and (iii) a population. D) (i) statistics, (ii) descriptive statistics, and (iii) a sample. E) (i) statistics, (ii) inferential statistics, and (iii) a population.

6) (i) The general process of gathering, organizing, presenting, analyzing, and interpreting data

to assist in making more effective decisions is called: (ii) The general process of analyzing, and interpreting data to assist in making more effective decisions is called: (iii) The subset of individuals or objects of interest or the measurements obtained from all individuals or objects of interest is called: A) (i) statistics, (ii) descriptive statistics, and (iii) a population. B) (i) descriptive statistics, (ii) inferential statistics, and (iii) a sample. C) (i) inferential statistics, (ii) descriptive statistics, and (iii) a population. D) (i) statistics, (ii) inferential statistics, and (iii) a sample. E) (i) statistics, (ii) inferential statistics, and (iii) a population.

7) (i) The general process of gathering, organizing, presenting, analyzing, and interpreting data

to assist in making more effective decisions is called: (ii) The general process of analyzing, and interpreting data to assist in making more effective decisions is called: (iii) If we test a small number of light bulbs from a large group, the small group is called a: A) (i) statistics, (ii) descriptive statistics, and (iii) a population. B) (i) descriptive statistics, (ii) inferential statistics, and (iii) a sample. C) (i) inferential statistics, (ii) descriptive statistics, and (iii) a population. D) (i) statistics, (ii) inferential statistics, and (iii) a sample. E) (i) statistics, (ii) inferential statistics, and (iii) a population.

8) (i) There are two types of variables-quantitative and qualitative.

(ii) A Qualitative variable is nonnumeric and we are usually interested in the number or percent of the observations from each category. (iii) Qualitative variables can be further divided into discrete and continuous variables. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

9) The main purpose of descriptive statistics is to: A) Summarize data in a useful and informative manner. B) Make inferences about a population. C) Determine if the data adequately represents the population. D) Gather or collect data.

10) When TV advertisements report that "2 out of 3 dentists surveyed indicated they would

recommend Brand X toothpaste to their patients," an informed consumer may question the conclusion because: A) The results were incorrectly computed. B) Dentists were not really surveyed. C) The conclusion does not include the total number of dentists surveyed. D) The conclusion is not illustrated with a graph.

11) What is a portion or part of a population called? A) Random sample B) Sample C) Tally D) Frequency distribution

A marketing class of 50 students evaluated the instructor using the following scale: superior, good, average, poor, and inferior. The descriptive summary showed the following survey results: 2% superior, 8% good, 45% average, 45% poor, and 0% inferior. E) The instructor's performance was great!!! F) The instructor's performance was inferior. G) Most students rated the instructor as poor or average. H) No conclusions can be made.

12) Which word is NOT part of the definition of descriptive statistics? A) Organizing B) Analyzing C) Presenting D) Predicting

13) A marketing class of 50 students evaluated the instructor using the following scale: superior,

good, average, poor, and inferior. The descriptive summary showed the following survey results: 42% superior, 28% good, 25% average, 5% poor, and 0% inferior. A) The instructor's performance was great!!! B) The instructor's performance was inferior. C) Most students rated the instructor as poor or average. D) No conclusions can be made.

14) Colleen Waite, Director of General Canadian Sales, is concerned by a downward sales trend.

Specifically, their customer base is stable at 2,200, but they are purchasing less each year. She orders her staff to search for causes of the downward trend by selecting a focus group of 50 customers. A) The focus group of 50 customers represents a sample. B) The focus group of 50 customers represents a population. C) The focus group of 50 customers represents an inferential statistic. D) The focus group of 50 customers represents a census.

15) Colleen Waite, Director of General Canadian Sales, is concerned by a downward sales trend.

Specifically, their customer base is stable at 2,200, but they are purchasing less each year. She orders her staff to search for causes of the downward trend by selecting a focus group of 50 customers. A) The 2,200 customers represent a sample. B) The 2,200 customers represent a population. C) The 2,200 customers represent an inferential statistic. D) The 2,200 customers represent a census.

16) What type of data is the number of litres of gasoline pumped by a filling station during a

day? A) B) C) D)

Qualitative Continuous Attribute Discrete

17) What type of data is the projected return on an investment? A) Qualitative B) Continuous C) Attribute D) Discrete

18) (i) There are two types of variables-quantitative and qualitative.

(ii) A Qualitative variable is nonnumeric and we are usually interested in the number or percent of the observations from each category. (iii) Quantitative variables can be further divided into discrete and continuous variables. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) Only statement (ii) is true.

19) What type of data is the number of robberies reported in your city? A) Attribute B) Continuous C) Discrete D) Qualitative

20) A survey reports consumers' preferred brands of dish soap. What type of data is this called? A) Quantitative B) Continuous C) Discrete D) Qualitative

21) Which of the following is an example of attribute data? A) Number of children in a family B) Weight of a person C) Colour of ink in a pen D) Miles between oil changes

22) A survey reports consumers' preferred hair colour. What type of data is this called? A) Attribute or Qualitative B) Continuous C) Discrete D) Quantitative

23) (i) There are two types of variables-quantitative and qualitative.

24) Your height and weight are examples of which type of random variable? A) Discrete B) Continuous C) Mutually exclusive D) Qualitative

25) What type of data is the amount of income tax that you have paid? A) Mutually exhaustive B) Continuous C) Discrete D) Qualitative

26) A market researcher is interested in determining the average income for families in York

Region, Ontario. To accomplish this, he takes a random sample of 200 families from the region and uses the data gathered to estimate the average income for families of the entire region. This process is an example of: A) descriptive statistics B) inferential statistics C) mutually exclusive statistics D) qualitative E) parametric methods

27) Which one of the following statistics is NOT an example of discrete data? A) Number of households watching Canadian Idol. B) Number of employees reporting in sick. C) Distance traveled between Toronto and Ottawa. D) Number of members of the York Region Lions Club. E) Number of family members.

28) Which of the following is an example of continuous data? A) Family income B) Number of students in a statistics class C) Postal codes of shoppers D) Rankings of baseball teams in a league

29) The incomes of a group of 50 loan applicants are obtained. Which level of measurement is

income? A) Nominal B) Ordinal C) Interval D) Ratio A bank asks customers to evaluate the drive-thru service as to good, average, or poor. Which level of measurement is this classification? E) Nominal F) Ordinal G) Interval H) Ratio

30) If Gallup, Harris and other pollsters asked people to indicate their political party affiliation-

Liberal, Conservative or NDP, the data gathered would be an example of which scale of measurement? A) Nominal B) Ordinal C) Interval D) Ratio

31) The members of each basketball team wear numbers on the back of their jerseys. What scale

of measurement are these numbers considered? A) Nominal B) Ordinal C) Interval D) Ratio

32) A questionnaire contained a question regarding marital status. The respondent checked

single, married, divorced, separated or widowed. What is the scale of measurement for this question? A) Ratio B) Interval C) Ordinal D) Nominal

33) Respondents were asked, "Do you now earn more than or less than you did five years ago?"

What is this level of measurement? A) Interval B) Ratio C) Nominal D) Ordinal

34) If unemployment is 5.5% of the population, what is this level of measurement? A) Nominal B) Ordinal C) Interval or ratio D) Descriptive

35) The Equal Employment Opportunity Act requires employers to classify their employees by

gender and national origin. Which level of measurement is this? A) Nominal B) Ordinal C) Interval D) Ratio

36) What level of measurement are the Centigrade and Fahrenheit temperature scales? A) Nominal B) Ordinal C) Interval D) Ratio

37) What level of measurement is the number of auto accidents reported in a given month? A) Nominal B) Ordinal C) Interval D) Ratio

38) The names of the positions on a hockey team, such as forward and defence, are examples of

what level of measurement? A) Nominal B) Ordinal C) Interval D) Ratio

39) What level of measurement is the price of an admission ticket to a movie theater? A) Nominal B) Ordinal C) Interval D) Ratio

40) The final rankings of the top 20 NCAA college basketball teams are an example of which

level of measurement? A) Nominal B) Ordinal C) Interval D) Ratio

41) Your height and weight are examples of which level of measurement? A) Nominal B) Ordinal C) Interval D) Ratio

42) Shoe sizes, such as 7B, 10D and 12EEE, are examples of what level of measurement? A) Nominal B) Ordinal C) Interval D) Ratio

43) The Nielsen Ratings break down the number of people watching a particular television show

by age. Age is what level of measurement? A) Nominal B) Ordinal C) Interval D) Ratio

44) What level of measurement is a bar code? A) Ratio B) Ordinal C) Interval D) Nominal

45) A group of women tried five brands of hair spray and ranked them according to preference.

What level of measurement is this? A) Nominal B) Ordinal C) Interval D) Ratio

46) Which of the following three statements are true?

(i) Statistics is defined as a body of techniques used to facilitate the collection, organization, presentation, analysis and interpretation of information for the purpose of making better decisions. (ii) The order that runners finish in a race would be an example of continuous data. (iii) The principal difference between the interval and ratio scale is that the ratio scale has a meaningful zero point. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

47) (i) If we select 100 persons out of 25,000 registered voters and question them about

candidates and issues, the 100 persons are referred to as the population. (ii) The order that runners finish in a race would be an example of continuous data. (iii) Qualitative data are usually summarized in graphs and bar charts. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (iii) only is correct.

48) A company was studying the demographics of their customers. As part of the study they

collected the following variables: gender, marital status, credit rating (low, medium, high), annual income, and age.

48.1)

Label the variable gender as qualitative or quantitative, discrete or continuous, and nominal, ordinal, interval, or ratio. A) qualitative, discrete, nominal B) qualitative, continuous, ordinal C) quantitative, discrete, nominal D) quantitative, continuous, ratio

48.2)

Label the variable marital status as qualitative or quantitative, discrete or continuous, and nominal, ordinal, interval, or ratio. A) qualitative, discrete, nominal B) qualitative, continuous, ordinal C) quantitative, discrete, nominal D) quantitative, continuous, ratio

48.3)

Label the variable credit rating as qualitative or quantitative, discrete or continuous, and nominal, ordinal, interval, or ratio. A) qualitative, continuous, nominal B) qualitative, discrete, ordinal C) quantitative, discrete, nominal D) quantitative, continuous, ratio

48.4)

Label the variable annual income as qualitative or quantitative, discrete or continuous, and nominal, ordinal, interval, or ratio. A) qualitative, discrete, nominal B) qualitative, continuous, ordinal C) quantitative, discrete, nominal D) quantitative, continuous, ratio

48.5)

Label the variable age as qualitative or quantitative, discrete or continuous, and nominal, ordinal, interval, or ratio. A) qualitative, discrete, nominal B) qualitative, continuous, Ordinal C) quantitative, discrete, nominal D) quantitative, continuous, ratio

48.6)

Which two variables are considered to be continuous rather than discrete? A) gender and marital status B) age and credit rating C) gender and annual income D) annual income and age

48.7)

Which two variables are considered to be quantitative rather than qualitative? A) gender and marital status B) age and credit rating C) gender and annual income D) annual income and age

48.8)

Which three variables are considered to be qualitative rather than quantitative? A) gender, age and marital status B) annual income, age and credit rating C) credit rating, gender, and marital status D) gender, annual income, and age

49) The collecting, organizing, presenting, analyzing, and interpreting of data is called: A) discrete information B) sample information C) descriptive information D) statistics

50) The branch of statistics which does not involve generalizations is called: A) discrete statistics B) sample statistics C) descriptive statistics D) inferential statistics

51) When we make an estimate or prediction, we use _____________ techniques. A) discrete B) sample C) descriptive D) inferential

52) The branch of statistics from which we draw conclusions from sample data is called

___________ statistics. A) discrete B) sample C) descriptive D) inferential

53) If we test a small number of light bulbs from a large group, the small group is called a: A) discrete B) sample C) descriptive D) population

54) The branch of statistics in which data is collected, analyzed and presented in a concise format

is called __________ statistics. A) discrete B) sample C) descriptive D) inferential

55) Among the many classes held at your college or university, your statistics class has been

selected for a study. This one class is referred to as a: A) discrete B) sample C) census D) population

56) The collection of all possible objects of interest is referred to as the: A) discrete B) sample C) census D) population

57) The total group being studied is called the: A) discrete B) sample C) census D) population

58) The number of workers reporting sick in any particular week is considered to be

____________ data. A) discrete B) continuous C) census D) population

59) A variable that can have any value within a specific range is called: A) discrete B) continuous C) census D) population

60) Ranked data is an example of a(n) ____________ level of measurement. A) nominal B) ordinal C) interval D) ratio

61) The prime rate of interest is an example of a(n) _____________ level of measurement. A) nominal B) ordinal C) interval D) ratio

62) The "lowest" level of measurement is: A) nominal B) ordinal C) interval D) ratio

63) The "highest" level of measurement is: A) nominal B) ordinal C) interval D) ratio

64) Categorizing students as freshmen, sophomores, juniors and seniors is an example of the

__________ level of measurement. A) nominal B) ordinal C) interval D) ratio

65) The lowest level of measurement that has some sort of ranking is: A) nominal B) ordinal C) interval D) ratio

66) PlayTime Toys Inc. employs 50 people in the Assembly Department. Forty of the employees

belong to a union and 10 do not. Five employees are selected at random to form a committee to meet with management regarding shift starting times.

66.1)

Would the 50 employees be considered a population or a sample? A) population B) sample

66.2)

Would the 5 selected employees be considered a population or a sample? A) population B) sample

67) The Shell station on Portage Ave in Winnipeg is studying the number of litres of fuel that are

sold on each day of the week. Records are available for the past year.

67.1)

How can the variable ‘number of litres' be best described? A) Discrete B) Quantitative C) Qualitative D) Census E) Nominal

67.2)

How can the variable ‘number of litres' be best described? A) Discrete B) Continuous C) Qualitative D) Census E) Nominal

67.3)

Is the variable ‘number of litres' discrete or continuous? A) Discrete B) Continuous

68) Environment Yukon tracks the changes in temperature in glaciers. Which answer best

describes this variable? A) Qualitative Nominal B) Qualitative Ordinal C) Quantitative Interval D) Quantitative Ratio

69) Environment Yukon tracks the changes in temperature in glaciers. Which answer best

describes this variable? A) discrete B) continuous C) nominal D) ordinal

70) A radio station conducts a survey to determine listener's favorite program. The choices are:

Talk radio, Sports Radio, Adult soft, Adult pop. Which answer best describes this variable? A) quantitative B) continuous C) nominal D) ordinal

71) Determine which answer best describes the new minimum wage amount of $16.00. A) Discrete ratio B) Continuous ratio C) Discrete interval D) Continuous interval

72) The number of cars parked at the hospital parking lot is? A) Nominal B) Ordinal C) Interval D) Ratio

73) A student receives the following grades: B+, C+, A, B+ and A+. What type of data has been

collected? A) Nominal B) Ordinal C) Interval D) Ratio

74) What type of variable is the number of cars parked at the hospital parking lot? A) Qualitative discrete B) Qualitative continuous C) Quantitative discrete D) Quantitative continuous

75) A telephone company asks you how many phones you have on your family plan. Which level

of measurement is this classification? A) Nominal B) Ordinal C) Interval D) Ratio

76) Today's weather report indicates an 80% chance of precipitation. Which level of

measurement is this classification? A) Nominal B) Ordinal C) Interval D) Ratio

77) Today's weather report indicates a high of 28 degrees. Which level of measurement is this

classification? A) Nominal B) Ordinal C) Interval D) Ratio

78) (i) Comparing temperatures from one period to another is looking at continuous ratio level

data. (ii) Comparing temperatures form one period to another is looking at continuous, interval level data. (iii) Comparing temperatures from one period to another is interval level data because a temperature still exists when the temperature is zero degrees. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i).

Answer Key Test name: chapter 1 1) A 2) C 3) A 4) B 5) E 6) D 7) D 8) B 9) A 10) C 11) B 12) C 13) D 14) A 15) A 16) B 17) B 18) B 19) A 20) C 21) D 22) C 23) A 24) A 25) B 26) B 27) B 28) C 29) A 30) D 31) B 32) A 33) A 34) D 35) D 36) C 37) A

38) C 39) D 40) A 41) D 42) B 43) D 44) B 45) D 46) D 47) B 48) C 49) D 50) Section Break 50.1) A 50.2) A 50.3) B 50.4) D 50.5) D 50.6) D 50.7) D 50.8) C 51) D 52) C 53) D 54) D 55) B 56) C 57) B 58) D 59) D 60) A 61) B 62) B 63) D 64) A 65) D 66) B 67) B 68) Section Break 68.1) A

68.2) B 69) Section Break 69.1) B 69.2) B 69.3) B 70) C 71) B 72) C 73) B 74) D 75) B 76) C 77) D 78) D 79) C 80) C

Student name:__________ 79) (i) A frequency table is a grouping of qualitative data into mutually exclusive classes

showing the number of observations in each class. (ii) Simple bar charts may be constructed either horizontally or vertically. (iii) A relative frequency table shows the fraction or percent of the number of observations in each class. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

80) (i) A frequency table is a grouping of qualitative data into mutually exclusive classes

showing the number of observations in each class. (ii) Simple bar charts may be constructed either horizontally or vertically. (iii) A bar chart is a graphic representation of a frequency table. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

81) (i) Pie charts are useful for showing the percent that various components compose of the

total. (ii) Simple bar charts may be constructed either horizontally or vertically. (iii) A bar chart is a graphic representation of a frequency table. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

82) (i) Bar charts are useful for showing the percent that various components compose of the

83) (i) Bar charts are useful for showing the percent that various components compose of the

total. (ii) Simple bar charts may be constructed either horizontally or vertically. (iii) A frequency polygon is ideal for showing the trend or sales of income over time. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

84) Using the frequency table below, determine the relative frequencies for Apartment and

Townhouse listings. Type

Number Of Listings

Apartment

House

Townhouse

14 98

A) B) C) D) E)

14% and 59% 27% and 14% 14% and 27% 59% and 27% 59% and 14%

85) Quinn's Café serves ice cream. She asks 100 of her regular customers to take a taste test and

pick the flavour they like the best. The results are shown in the following table. Flavour

Number

Vanilla

Green tea

Lemon

Coffee

Total

100

Is the data quantitative or qualitative? What is the name of the table shown? A) quantitative, simple table B) quantitative, frequency table C) qualitative, frequency table D) qualitative, cumulative frequency distribution E) quantitative, bar chart

86) When data is collected using a qualitative, nominal variable, i.e., male or female, what is true

about a frequency distribution that summarizes the data? A) Upper and lower class limits must be calculated. B) Class midpoints can be computed. C) Number of classes corresponds to number of the variable's values. D) The "2 to the k rule" can be applied.

87) A student was interested in the cigarette smoking habits of college students and collected

data from an unbiased random sample of students. The data is summarized in the following table: Male:50

Female:75

Males who smoke: 20

Females who smoke: 25

Males who do not smoke: 30

Females who do not smoke: 50

Why is the table NOT a frequency table? A) The number of males does not equal the sum of males that smoke and do not smoke. B) The classes are not mutually exclusive. C) There are too many classes. D) Class limits cannot be computed

88) A group of 100 students were surveyed about their interest in a new International Studies

program. The survey asked students about their interest in the program in terms of high, medium, or low. 30 students responded high interest; 50 students responded medium interest; 20 students responded low interest. What is the relative frequency of students with low interest? A) 30% B) 50% C) 20% D) Cannot be determined.

89) Which of the following would be most helpful if you wished to construct a pie chart? A) a frequency distribution B) a relative frequency table C) a cumulative frequency distribution D) an ogive E) a clustered bar chart

90) (i) A frequency distribution is grouping of data into classes showing the number of

observations in each class. (ii) The midpoint of a class, which is also called a class mark, is halfway between the lower and upper limits. (iii) A class interval, which is the width of a class, can be determined by subtracting the lower limit of a class from the lower limit of the next higher class. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

91) (i) A frequency distribution is grouping of data into classes showing the number of

observations in each class. (ii) In constructing a frequency distribution, you should try to have open-ended classes such as "Under $100" and "$1,000 and over". (iii) A cumulative frequency distribution is used when we want to determine how many observations lie above or below certain values. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i).

92) Monthly commissions of first-year insurance brokers are $1,270, $1,310, $1,680, $1,380,

$1,410, $1,570, $1,180 and $1,420. These figures are referred to as: A) histogram. B) raw data. C) frequency distribution. D) frequency polygon.

93) The weekly incomes of a small sample of computer operators are $1,950, $1,775, $2,060,

$1,840, $1,795, $1,890, $1,925 and $1,810. What are these ungrouped numbers called? A) Histogram B) Class limits C) Class frequencies D) Raw data

94) A group of 100 students were surveyed about their interest in a new International Studies

program. The survey asked students about their interest in the program in terms of high, medium, or low. 30 students responded high interest; 50 students responded medium interest; 20 students responded low interest. What is the relative frequency of students with high interest? A) 30% B) 50% C) 20% D) Cannot be determined.

95) When a class interval is expressed as: 100 to under 200 A) Observations with values of 100 are excluded from the class frequency. B) Observations with values of 200 are included in the class frequency. C) Observations with values of 200 are excluded from the class frequency. D) The class interval is 99.

96) What is the following table called?

A) B) C) D)

Ages

Number of Ages

20 to under 30

30 to under 40

40 to under 50

50 to under 60

60 to under 70

70 to under 80

Histogram Frequency polygon Cumulative frequency distribution Frequency distribution

97) A group of 100 students were surveyed about their interest in a new International Studies

98) The monthly salaries of a sample of 100 employees were rounded to the nearest ten dollars.

They ranged from a low of $1,040 to a high of $1,720. If we want to condense the data into seven classes, what is the most convenient class interval? A) $50 B) $100 C) $150 D) $200

99) For the following distribution of heights, what are the limits for the class with the greatest

frequency? Heights

60” to under 65”

65” to under 70”

70” to under 75”

Number

A) B) C) D)

64 and 70 65 and 69 65 and 70 69.5 and 74.5

100)

In a frequency distribution, what is the number of observations in a class called? A) Class midpoint B) Class interval C) Class array D) Class frequency

101)

A sample distribution of hourly earnings in Paul's Cookie Factory is: Hourly Earnings

$9 to under $12

$12 to under $15

$15 to under $18

Numbers

The limits of the class with the smallest frequency are: A) $9.00 and $12.00 B) $16.00 and $18.00 C) $12 and $15 D) $15.00 and $18.00

102)

Why are unequal class intervals sometimes used in a frequency distribution? A) To avoid a large number of empty classes B) For the sake of variety in presenting the data C) To make the class frequencies smaller D) To avoid the need for midpoints

103)

Consider the following relative frequency distribution: Class Interval

Relative Frequency

0 to under 10

0.2

10 to under 20

0.3

20 to under 30

0.45

30 to under 40

0.05

If there are 2,000 numbers in the data set, how many of the values are less than 30? A) 900 B) 90 C) 1900 D) 100

104)

Refer to the following price of jeans are recorded to the nearest dollar:

The first two class midpoints are $62.50 and $65.50.

104.1) What is the class interval? A) $1.00 B) $2.00 C) $2.50 D) $3.00

104.2) What are the class limits for the lowest class? A) $61 and up to $64 B) $62 and up to $64 C) $62 and $65 D) $62 and $63

104.3) What are the class limits for the third class? A) $64 and $67 B) $67 and $69 C) $67 and $70 D) $66 and $68

105)

Refer to the following ages (rounded to the nearest whole year) of employees at a large company that were grouped into a distribution with class limits: 20 up to 30 30 up to 40 40 up to 50 50 up to 60 60 up to 70 What is the class interval and the midpoint of the first class? A) 20 and 25 B) 20 and 24.5 C) 10 and 25 D) 10 and 24.5

106)

What is the class midpoint for the $45 up to $55 class?

A) B) C) D)

49 49.5 50 50.5

Cost of Textbooks

Number

$25 up to $35

35 up to 45

45 up to 55

55 up to 65

65 up to 75

107)

What are the class limits for the $55 up to $65 class?

A) B) C) D)

Cost of Textbooks

Number

$25 up to $35

35 up to 45

45 up to 55

55 up to 65

65 up to 75

55 and 64 54 and 64 55 and up to 65 55 and 64.5

108)

The following class intervals for a frequency distribution were developed to provide information regarding the starting salaries for students graduating from a particular school: Salary ($1,000s )

Number of Graduates

18-under 21

21-under 25

24-under 27

29-under 30

108.1) Before data was collected, someone questioned the validity of this arrangement. Which of

the following represents a problem with this set of intervals? A) there are too many intervals B) the class widths are too small C) some numbers between 18,000 and 30,000 would fall into two different intervals D) the first and the second interval overlap

108.2) Before data was collected, someone questioned the validity of this arrangement. Which of

the following represents a problem with this set of intervals? A) there are too many intervals B) the class widths are too small C) some numbers between 18,000 and 30,000 would not fall into any of these intervals D) the first and the second intervals overlap E) the second and third intervals overlap

109)

The head of the statistics department wants to determine the number of mistake made by students in their first online assignment. She gathers information from her classes of the past year. Errors Per Assignment

Number of Students

0 to under 2

2 to under 4

4 to under 6

6 to under 8

8 to under 10

The approximate range (distance from the minimum value in the raw data up to the maximum value) of the data is: A) 150 B) 40 C) 10 D) 2

110)

Refer to the following distribution of commissions: Monthly commissions

Class Frequencies

$600 to under $800

800 to under 1,000

1,000 to under 1,200

1,200 to under 1,400

1,400 to under 1,600

1,600 to under 1,800

1,800 to under 2,000

2,000 to under 2,200

110.1) What is the relative frequency for those salespersons that earn between $1,600 and

$1,799? A) 2% B) 2.4% C) 20% D) 24%

110.2) The first plot for a cumulative greater than frequency distribution should be: A) X = 0, Y = 600. B) X = 600, Y = 3. C) X = 3, Y = 600. D) X = 600, Y = 120.

110.3) What is the relative frequency of those salespersons that earn more than $1,599? A) 25.5% B) 27.5% C) 29.5% D) 30.8%

110.4) What is the relative frequency for those salespersons that earn between $1,500 and

$1,800? A) 2% B) 2.4% C) 20% D) 24% E) Unable to determine without approximation

111)

(i) Simple bar charts may be constructed either horizontally or vertically. (ii) A frequency polygon is a very useful graphic technique when comparing two or more distributions (iii) A cumulative frequency distribution is used when we want to determine how many observations lie above or below certain values. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

112)

One rule that must always be followed in constructing frequency distributions is that: A) the number of classes must be less than 10. B) each data point can only fall into one class. C) the width of each class is equal to the range. D) the number of intervals must be an odd number. E) the class intervals must overlap.

113)

Refer to the following chart showing a distribution of exporting firms: Exports ($ millions )

Number of Firms

$1 to under $4

4 to under 7

7 to under 10

10 to under 13

13 to under 16

113.1) For the distribution above, what is the midpoint of the class with the greatest frequency? A) $6 million B) $8.5 million C) $10.0 million D) The midpoint cannot be determined

113.2) What is the class interval? A) 2 B) 3 C) 3.5 D) 4

113.3) How many firms export less than $13 million in product? A) 10 B) 60 C) 50 D) 49

113.4) What percentage of the firms export less than $13 million in product? A) 3% B) 6% C) 49% D) 94% E) 75%

114)

Refer to the following distribution of commissions: Monthly commissions

Class frequencies

$600 to under $800

800 to under 1,000

1,000 to under 1,200

1,200 to under 1,400

1,400 to under 1,600

1,600 to under 1,800

1,800 to under 2,000

2,000 to under 2,200

114.1) What is the class interval for the table of commissions above? A) $200 B) $300 C) $400 D) $1600

114.2) What is the class midpoint for the class with the greatest frequency? A) $1400 B) $1500 C) $1600 D) $1700

114.3) What are the class limits for the class with the smallest number of frequencies? A) 600 and 800 B) 800 and 1000 C) 2000 and 2200 D) 599 and 799

115)

Refer to the following distribution of ages: Ages

Number

40 up to 50

50 up to 60

60 up to 70

115.1) For the distribution of ages above, what is the relative class frequency for the lowest

class? A) B) C) D)

50% 18% 20% 10%

115.2) What is the class interval? A) 9 B) 10 C) 10.5 D) 11

115.3) What is the class midpoint of the lowest class? A) 45 B) 50 C) 55 D) 65

116)

Refer to the following frequency distribution on days absent during a calendar year by employees of a manufacturing company: Days Absent

Number of Employees

0 to under 3

3 to under 6

6 to under 9

9 to under 12

12 to under 15

116.1) How many employees were absent between 3 to under 6 days? A) 31 B) 29 C) 14 D) 2 E) 17

116.2) How many employees were absent fewer than six days? A) 60 B) 31 C) 91 D) 46

116.3) How many employees were absent six or more days? A) 8 B) 4 C) 22 D) 31

116.4) How many employees were absent from 6 to under 12 days? A) 20 B) 8 C) 12 D) 17

117)

(i) Pie charts are useful for showing the percent that various components compose of the total. (ii) Simple bar charts may be constructed either horizontally or vertically. (iii) A Frequency Polygon is ideal for showing the trend or sales of income over time. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all incorrect statements.

118)

(i) In constructing a frequency distribution, you should try to have open-ended classes such as "Under $100" and "$1,000 and over". (ii) To convert a frequency distribution to a relative frequency distribution, divide each class frequency by the sum of the class frequencies. (iii) When constructing a frequency distribution, try to include overlapping stated class limits, such as 100 up to 201, 200 up to 301, and 300 up to 401. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) is a correct statement but not (i) or (iii). E) (i), (ii) and (iii) are all false statements.

119)

What is the relative class frequency for the $25 up to $35 class?

A) B) C) D)

2% 4% 5% 10%

Cost of Textbooks

Number

$25 up to $35

35 up to 45

45 up to 55

55 up to 65

65 up to 75

120)

The relative frequency for a class is computed as A) Class width divided by class interval. B) Class midpoint divided by the class frequency. C) Class frequency divided by the class interval. D) Class frequency divided by the total frequency.

121)

When a class interval is expressed as: 100 to under 200 (i) Observations with values of 100 are included from the class frequency. (ii) Observations with values of 200 are included in the class frequency. (iii) Observations with values of 200 are excluded from the class frequency. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) is a correct statement but not (i) or (iii).

122)

The age distribution of a sample of the part-time employees at Lloyd's Fast Food Emporium is: Ages

Number

18 up to 23

23 up to 28

19 %

28 up to 33

52 %

33 up to 38

20 %

38 up to 43

What type of chart has the data been organized to draw? A) Histogram B) Simple frequency polygon C) Relative frequency polygon D) Pie chart E) Less than cumulative frequency polygon

123)

In a simple Frequency Polygon, where is time plotted? A) On the X-axis B) On the Y-axis C) On either axis D) Never plotted

124)

The grades on a statistics exam for a sample of students are as follows: Stem

Leaf

1278

156789

122457888

1156799

12467

If A + = 90% - 100% A = 80% - 89% B+ = 75% - 79% B = 70% - 74% C+ = 65% - 69% C = 60% - 64% D+ = 55% - 59% D = 50% - 54% F = 0 - 49%

124.1) What is the most common letter grade earned? A) A (80%-89%) B) B (70%-74%) C) C (60%-64%) D) D (50%-54%) E) F (0-49%)

124.2) What is the most common letter grade earned? A) A (80%-100%) B) B (70%-79%) C) C (60%-69%) D) D (50%-59%) E) F (0-49%)

124.3) What is the most common letter grade earned? A) A (80%-89%) B) B (70%-74%) C) C (60%-64%) D) D (50%-54%) E) F (0-49%)

125)

(i) For a stem-and-leaf display, the leaf for the value 98 is 9. (ii) There is some loss of information when raw data is tallied into a stem-and-leaf display. (iii) A cumulative frequency distribution is used when we want to determine how many observations lie above or below certain values. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (iii) is a correct statement but not (i) or (ii) E) (i), (ii) and (iii) are all false statements.

126)

The grades on a statistics exam for a sample of students are as follows: Stem

Leaf

1278

156789

1224578889

1156799

1246

If A + = 90% - 100% A = 80% - 89% B+ = 75% - 79% B = 70% - 74% C+ = 65% - 69% C = 60% - 64% D = 55% - 59% F = 0% - 54%

126.1) How many students wrote this test? A) 36 B) 35 C) 38 D) 7 E) 43

126.2) How many student earned a letter grade of C? A) 1 B) 3 C) 4 D) 5 E) 10

127)

A row of a stem-and-leaf chart appears as follows: 3 | 0 1 3 5 7 9. Assume that the data is rounded to the nearest unit. A) The frequency of the class is seven. B) The minimum value in the class is 0. C) The maximum value in the class could be 39. D) The class interval is 5.

128)

(i). The stem in a stem-and-leaf display is the leading digit (ii) There is no loss of information when raw data is tallied into a stem-and-leaf display. (iii). For a stem-and-leaf display, the leaf for the value 98 is 9 A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

129)

Given the following stem and leaf plot, determine the smallest value in the data set. Frequency

Stem

Leaf

677

0222257899

0667788

223444556788

000011357

45 A) B) C) D) E)

1 19 199 45 2

130)

Given the following stem and leaf plot, determine the largest value in the data set. Frequency

Stem

Leaf

677

0222257899

0667788

223444556788

000011357

45 A) B) C) D) E)

131)

87 819 28 17 817

The following represent the ages of students in a class:

19, 23, 21, 19, 19, 20, 22, 31, 21, 20

131.1) If a stem and leaf plot were to be developed from this, how many stems would there be? A) 1 B) 2 C) 3 D) 4 E) 10

131.2) If a stem and leaf plot were to be developed from this, how many leaves would there be

off the second stem? A) 11 B) 2 C) 3 D) 4 E) 6

132)

Consider the following stem and leaf plot: 0

033578

146

222

Suppose that you decided to develop a frequency distribution from this plot. What would be the lower limit of the first class? A) 0 B) 10 C) 11 D) 1 E) 3

133)

In constructing a frequency polygon, the class frequencies are scaled on the: A) X-axis B) Y-axis C) Z-axis

134)

A useful chart or graph to use for illustrating relative frequencies is the: A) bar chart B) pie chart C) clustered bar chart D) multiple line polygon

135)

(i) A table showing the number of observations that have been grouped into each of several classes is called a frequency distribution. (ii) When classes in a frequency table are constructed so that data will fit into only one category, it is called a relative class frequency. (iii) The suggested class interval based on number of observations given the data ranges from 100 to 200 with 50 observations is 50. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and (iii) are correct statements but not (ii). D) (i) is a correct statement but not (ii) or (iii).

136)

(i) A table showing the number of observations that have been grouped into each of several classes is called a frequency distribution. (ii) When classes in a frequency table are constructed so that data will fit into only one category, it is called mutually exclusive. (iii) The suggested class interval based on number of observations given the data ranges from 100 to 200 with 50 observations is 20 A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i).

137)

(i) A table showing the number of observations that have been grouped into each of several classes is called a frequency distribution. (ii) When classes in a frequency table are constructed so that data will fit into only one category, it is called mutually exclusive. (iii) The best means to display data that is based on a trend over a period of time is the polygon. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i).

138)

(i) If you are constructing a stem-and-leaf display, the "20" in 20.5 would be the stem. (ii) An advantage of a stem-and-leaf chart over a histogram is that the identity of each observation is not lost, and that it presents a picture of the distribution. (iii) An advantage of a stem-and-leaf chart over a histogram is that it presents a picture of the distribution. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i).

139)

(i) If you are constructing a stem-and-leaf display, the "20" in 20.5 would be the stem. (ii) An advantage of a stem-and-leaf chart over a histogram is that the identity of each observation is not lost, and that it presents a picture of the distribution. (iii) If you are constructing a stem-and-leaf display, the "20" in 20.5 would be the leaf. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and, (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i).

140)

(i) If you are constructing a stem-and-leaf display, the "20" in 20.5 would be the stem. (ii) An advantage of a stem-and-leaf chart over a histogram is that the identity of each observation is not lost, and that it presents a picture of the distribution. (iii) If you are constructing a stem-and-leaf display, the "2" in 20.5 would be the leaf. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i).

141)

The following ages (rounded to the nearest whole year) of employees at a large company that were grouped into a distribution with class limits: 20 up to 30 30 up to 40 40 up to 50 50 up to 60 60 up to 70

141.1) (i) The class limits for the class 50 up to 60 class are 50 and 58.

(ii) The midpoint for the class 40 up to 50 is 45. (iii) The class interval is 9. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (ii) is correct but not not (i) and (iii). D) (ii) and (iii) are correct statements but not (i).

141.2) (i) The class limits for the class 50 up to 60 class are 50 and 58.

(ii) The midpoint for the class 40 up to 50 is 45. (iii) The class interval is 10. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i).

141.3) (i) The class limits for the class 50 up to 60 class are 50 and 60.

141.4) (i) The class limits for the class 50 up to 60 class are 50 and 58.

(ii) The midpoint for the class 40 up to 50 is 40. (iii) The class interval is 9. A) (i), (ii) and (iii) are all correct statements. B) (i), (ii) and (iii) are all false statements. C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i).

142)

A student was studying the political party preferences of a university's student population. The survey instrument asked students to identify themselves as a Conservative or NDP. This question is flawed because: A) Students generally don't know their political preferences. B) The categories are generally mutually exclusive. C) The categories are not exhaustive. D) Political preference is a continuous variable.

143)

The following represent the online deliveries made by a selection of businesses throughout the city: 73,50,42,46,51,48,75 55,70,54,44,50

143.1) If a stem and leaf plot were to be developed from this, how many leafs would there be? A) 4 B) 5 C) 10 D) 11 E) 12

143.2) If a stem and leaf plot were to be developed from this, how many stems would there be? A) 2 B) 3 C) 4 D) 6 E) 12

144)

During the pandemic the number of Covid-19 new cases reported during the fourth wave were as follows: Stem

Leaf

01488

3699

014567889

11145569

12 13

144.1) How many days of new cases were observed? A) 6 B) 7 C) 13 D) 33 E) 139

144.2) What were the most common number of cases? A) 109 B) 111 C) 114 D) 139 E) 11

144.3) How many days were there over 120 cases? A) 0 B) 1 C) 2 D) 4 E) 5

14559

144.4) How many new cases were in the 3rd class? A) 0 B) 1 C) 2 D) 3 E) 4

144.5) Which class had the most new cases? A) 1 B) 2 C) 3 D) 4 E) 5

144.6) What is the middle value number of cases? A) 107 B) 109 C) 111 D) 115 E) 10

145)

Refer to the following frequency distribution on the number of hospitalizations during the fourth wave of the pandemic: Patients

Number of Days

0 to under 50

50 to under 100

100 to under 150

150 to under 200

Over 200

145.1) How many days were there between 100 to under 150 patients? A) 5 B) 89 C) 14 D) 36 E) 17

145.2) How many days were in the study? A) 0 B) 5 C) 36 D) 89 E) 200

145.3) What percent of the time were there less than 100 patients? A) 25% B) 50% C) 75% D) 100% E) Not available

145.4) What is the most likely number of patients? A) 0 to under 50 B) 50 to under 100 C) 100 to under 150 D) 150 to under 200 E) Over 200

Answer Key Test name: chapter 2 81) A 82) A 83) A 84) D 85) D 86) E 87) C 88) C 89) B 90) C 91) B 92) A 93) C 94) B 95) D 96) A 97) C 98) D 99) C 100) B 101) C 102) D 103) D 104) A 105) C 106) Section Break 106.1) D 106.2) A 106.3) C 107) C 108) C 109) C 110) Section Break 110.1) C 110.2) C 111) C 112) Section Break

112.1) C 112.2) D 112.3) D 112.4) E 113) A 114) B 115) Section Break 115.1) B 115.2) B 115.3) D 115.4) D 116) Section Break 116.1) A 116.2) B 116.3) A 117) Section Break 117.1) C 117.2) B 117.3) A 118) Section Break 118.1) A 118.2) C 118.3) C 118.4) A 119) A 120) D 121) B 122) D 123) C 124) C 125) A 126) Section Break 126.1) E 126.2) C 126.3) A 127) D 128) Section Break 128.1) B 128.2) C 129) C

130) B 131) B 132) A 133) Section Break 133.1) C 133.2) E 134) A 135) B 136) B 137) D 138) A 139) A 140) A 141) C 142) C 143) Section Break 143.1) C 143.2) D 143.3) A 143.4) B 144) C 145) Section Break 145.1) E 145.2) C 146) Section Break 146.1) D 146.2) B 146.3) E 146.4) E 146.5) D 146.6) A 147) Section Break 147.1) C 147.2) D 147.3) C 147.4) A

Student name:__________ 146)

i. A value that is typical or representative of the data is referred to as a measure of central tendency. ii. The arithmetic mean is the sum of the observations divided by the total number of observations iii. The value of the observation in the center after they have been arranged in numerical order is called the weighted mean A) (i), (ii), and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

147)

The following details real estate prices for Regina and surrounding areas in the early 2000s. List prices, Regina and surrounding area List Price (x000 )

Frequency

f*M

M2*f

50 to under 100

1050

78750

100 to under 150

125

2875

359375

150 to under 200

175

2800

490000

200 to under 250

225

4050

911250

250 to under 300

275

2200

605000

300 to under 350

325

1625

528125

350 to under 400

375

1500

562500

400 to under 450

425

850

361250

147.1) Using the information gathered for real estate prices in Regina and surrounding areas in

the early 2000's, determine the mean of the selling prices at that time. A) $188,330 B) $200,000 C) $125,000 D) $178,350 E) $195,600

147.2) Using the information gathered for real estate prices in Regina and surrounding areas in

the early 2000's, determine the median of the selling prices at that time. A) $188,330 B) $200,000 C) $125,000 D) $175,000 E) $195,600

147.3) Using the information gathered for real estate prices in Regina and surrounding areas in

the early 2000's, determine the standard deviation of the selling prices at that time. A) $88,330 B) $20,000 C) $25,000 D) $78,350 E) $88,939

148)

A sample of light trucks using diesel fuel revealed the following distribution based on fuel efficiency, i.e., litres per 100 km. Litres/100km

Number of Trucks

6 to under 9

9 to under 12

12 to under 15

15 to under 18

18 to under 21

21 to under 24

What is the arithmetic mean in litres per 100 km? A) 16.9 B) 14.6 C) 17.0 D) 17.9 E) Mean cannot be estimated.

149)

The ages of newly hired, unskilled employees were grouped into the following distribution: Ages

Number

18 to under 21

21 to under 24

24 to under 27

27 to under 30

30 to under 33

What is the median age? A) 28.50 B) 28.08 C) 25.08 D) 27.14 E) 27.30

150)

A sample of the daily production of transceivers was organized into the following distribution. Daily Production

Frequencies

80 to under 90

90 to under 100

100 to under 110

110 to under 120

120 to under 130

130 to under 140

What is the mean daily production? A) 86.4 B) 101.4 C) 111.4 D) 106.4 E) 20.0

151)

The net sales of a sample of small stamping plants were organized into the following percent frequency distribution. Net Sales (in $millions)

Percent of Total

1 to under 4

4 to under 7

7 to under 10

10 to under 13

13 or more

What is the mean net sales (in $millions)? A) $7.09 B) $10.09 C) $8.59 D) $8.34 E) Mean cannot be computed

152)

A stockbroker placed the following order for a customer:

-50 shares of Kaiser Aluminum preferred at $104 a share -100 shares of GTE preferred at $25 1/4 a share -20 shares of Boston Edison preferred at $9 1/8 a share What is the weighted arithmetic mean price per share? A) $25.25 B) $79.75 C) $103.50 D) $46.51 E) Weighted mean cannot be computed for this data set.

153)

During the past six months, the purchasing agent bought: Tons of Coal

1,200

3,000

500

Price per Ton

$28.50

$87.25

$88.00

What is the weighted arithmetic mean price per ton? A) $87.25 B) $72.33 C) $68.47 D) $89.18 E) Weighted mean cannot be computed for this data set.

154)

A sample of single persons receiving social security payments revealed these monthly benefits: $826, $699, $1,087, $880, $839 and $965. How many observations are below the median? A) 0 B) 1 C) 2 D) 3

155)

The number of work stoppages in a highly industrialized region for selected months are: 6, 0, 10, 14, 8 and 0. What is the median number of stoppages? A) 0 B) 6 C) 7 D) 8

156)

The Federal Aviation Administration reported that passenger revenues on international flights increased from $528 million in 2000 to $5,100 million in 2021. What is the geometric mean annual percent increase in international passenger revenues? A) 10.4 % B) 27.9% C) 100.4% D) 11.4%

157)

The Investment Company Institute reported in its Mutual Fund Fact Book that the number of mutual funds increased from 410 in 2010 to 857 in 2021. What is the geometric mean annual percent increase in the number of funds? A) 106.93% B) 6.93% C) 10.0% D) 48.66% E) Not available

158)

Assume a student received the following grades for the semester: History, B; Statistics, A; Spanish, C; and English, C. History and English are 5 credit hour courses, Statistics a 4 credit hour course and Spanish a 3 credit hour course. If 4 grade points are assigned for an A, 3 for a B and 2 for a C, what is the weighted mean for the semester grades? A) 4.00 B) 1.96 C) 2.76 D) 3.01 E) 2.88

159)

Production of passenger cars in Japan increased from 3.94 million in 2011 to 6.74 million in 2021. What is the geometric mean annual percent increase? A) 4.0% B) 1.9% C) 5.5% D) 16.6% E) 47.3%

160)

A sample of the paramedical fees charged by clinics revealed these amounts: $55, $49, $50, $45, $52 and $55. What is the median charge? A) $47.50 B) $51.00 C) $52.00 D) $55.00 E) $48.00

161)

The lengths of time (in minutes) several underwriters took to review applications for similar insurance coverage are: 50, 230, 52 and 57. What is the median length of time required to review an application? A) 54.5 B) 141.0 C) 97.25 D) 109.0 E) $55.40

162)

The U.S. Department of Education reported that for the past six years 23, 19, 15, 30, 27 and 25 women received doctorate degrees in computer and information sciences. What is the mean arithmetic annual number of women receiving this degree? A) 15.1 B) 23.2 C) 37.9 D) 22.9 E) $22.3

163)

A bottling company offers three kinds of delivery service - instant, same day and within five days. The profit per delivery varies according to the kind of delivery. The profit for an instant delivery is less than the other kinds because the driver has to go directly to a grocery store with a small load and return to the bottling plant. To find out what effect each type of delivery has on the profit picture, the company has made the following tabulation based on deliveries for the previous quarter. Type of Delivery

Number of Deliveries During the Quarter

Profit per Delivery

Instant

100

$70

Same day

100

Within five days

160

What is the weighted mean profit per delivery? A) $72 B) $100 C) $142 D) $97 E) $99

164)

The U.S. Department of Education reported that for the past seven years 4,033, 5,652, 6,407, 7,201, 8,719, 11,154, and 15,121 people received bachelor's degrees in computer and information sciences. What is the arithmetic mean annual number receiving this degree? A) About 12,240 B) About 8,327 C) About 6,217 D) About 15,962 E) About 8,399

165)

Which measure of central tendency is found by arranging the data from low to high, and selecting the middle value? A) Arithmetic mean B) Median C) Mode D) Geometric mean

166)

The number of students at a local university increased from 2,500 students to 5000 students in 10 years. Based on a geometric mean, the university grew at an average percentage rate of A) 2,500 students per year B) 1.0718 students per year C) 7.18 percent per year D) 250 students per year E) Cannot be determined

167)

A question in a market survey asks for a respondent's favourite car colour. Which measure of central tendency should be used to summarize this question? A) Mode B) Median C) Mean D) Geometric mean E) Weighted mean

168)

AAA Heating and Air Conditioning completed 30 jobs last month with a mean revenue of $5,430 per job. The president wants to know the total revenue for the month. A) Insufficient information to estimate. B) $5,430 C) $54,330 D) $162,900 E) $169,200

169)

Three persons earn $8 an hour, six earn $9 an hour, and one earns $12 an hour. Find the weighted mean hourly wage. A) $8 B) $9 C) $12 D) $6 E) $10

170)

171)

Which one of the following is referred to as the population mean? A) Statistic B) µ C) Sample D) ∑

If there are an odd number of observations in a set of ungrouped data that have been arrayed from low to high or vice versa, where is the median located? A) n B) n/2 C) (n + 1)/2 D) n + 1/2

172)

For which measure of central tendency will the sum of the deviations of each value from that average always be zero? A) Mode B) Mean C) Median D) Geometric mean E) The sum of the deviations of each value from that average will always be zero for all measures of central tendency.

173)

Which measure of central tendency is used to determine the average annual percent increase? A) Arithmetic mean B) Weighted mean C) Mode D) Geometric mean E) Median

174)

Fifteen accounting majors had an average grade of 90 on a finance exam. Seven marketing majors averaged 85, while ten finance majors averaged 93 on the same exam. What is the weighted mean for the 32 students taking the exam? A) 89.84 B) 89.33 C) 89.48 D) Impossible to determine without more information E) $89.88

175)

On a survey questionnaire, students were asked to indicate their class rank in college. If there were only four choices from which to choose, which measure(s) of central tendency would be appropriate to use for the data generated by that questionnaire item? A) Mean and median B) Mean and mode C) Mode and median D) Mode only E) Median only

176)

What is the median of 26, 30, 24, 32, 32, 31, 27 and 29? A) 32 B) 29 C) 30 D) 29.5 E) 30.5

177)

The net incomes (in $millions) of a sample of steel fabricators are: $86, $67, $86 and $85. What is the modal net income? A) $67 B) $85 C) $85.5 D) $86 E) $84

178)

i. A parameter is a measurable characteristic of a sample. ii. The weighted mean is the nth root of n observations. iii. A statistic is a measurable characteristic of the population. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

179)

Listed below is the average earnings ratio by sex for first-year, full-time workers from 2012 to 2021. Year

Women

Men

Earnings Ratio (% )

2012

$27000

$43000

62.6

2013

27500

44500

61.7

2014

27600

44400

62.1

2015

27900

44400

62.8

2016

27600

44800

62.9

2017

27900

44000

63.5

2018

28600

44700

64.0

2019

29000

44800

64.7.

2020

29900

45500

65.7

2021

30200

46900

64.5

179.1) What is the median earnings for women for the years 2012-2021? A) $27,000 B) $27,600 C) $27,900 D) $28,320 E) $28,600

179.2) What is the mean earnings for women for the years 2012 to 2021? A) $27,000 B) $27,600 C) $27,900 D) $28,320 E) $28,600

179.3) What were the modal earnings for women for the years 2012 to 2021? A) $27,000 B) $27,600 and $27,900 C) $28,320 D) $28,600

179.4) What is the median earnings for men for the years 2012 to 2021? A) $43,000 B) $44,400 C) $44,500 D) $44,600 E) $44,700

179.5) What is the mean earnings for men for the years 2012 to 2021? A) $43,000 B) $44,400 C) $44,500 D) $44,600 E) $44,700

179.6) What were the modal earnings for men for the years 2012 to 2021? A) $43,000 and $44,800 B) $44,400 and $44,800 C) $44,500 and $44,900 D) $44,600 and $44,800 E) $44,700 and $44,800

180)

i. For salaries of $102,000, $98,000, $25,000, $106,000 and $101,000, the arithmetic mean would be an appropriate average. ii. Extremely high or low scores affect the value of the median. iii. Three persons earn $8 an hour, six earn $9 an hour, and one earns $12 an hour. The weighted mean hourly wage is $10. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

181)

i. For salaries of $102,000, $98,000, $35,000, $106,000 and $101,000, the arithmetic mean would be an appropriate average. ii. Extremely high or low scores do not affect the value of the median. iii. Three persons earn $8 an hour, six earn $9 an hour, and one earns $12 an hour. The weighted mean hourly wage is $9. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

182)

i. For salaries of $102,000, $98,000, $25,000, $106,000 and $101,000, the median would be an appropriate average. ii. There are always as many values above the mean as below it. iii. Three persons earn $8 an hour, six earn $9 an hour, and one earns $12 an hour. The weighted mean hourly wage is $9. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

183)

Referring to the printout below, describe the shape of the distribution of the corresponding histogram. Class

A) B) C) D)

184)

Grades

count

mean

71.8

minimum

14.3

maximum

99.2

range

coefficient of variation (CV)

30.67%

1 quartile

58.25

median

77.25

3 quartile

89.91

interquartile range

31.67

mode

82.0

Positively skewed Negatively skewed Perfectly symmetrical Statistical

i. If there is an even number of ungrouped values, then half of the values will be less than the median. ii. Extremely high or low scores affect the value of the median. iii. There are always as many values above the mean as below it. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

185)

i. If there is an even number of ungrouped values, then half of the values will be less than the median. ii. Extremely high or low scores do not affect the value of the median. iii. There are always as many values above the mean as below it. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

186)

Sometimes, data has two values that have the highest and equal frequencies. In this case, the distribution of the data can best be summarized as A) symmetric B) bimodal (having two modes) C) positively skewed D) negatively skewed E) continuous

187)

Which measures of central tendency always have but one value for a set of grouped or ungrouped data? A) Mode and median B) Mode and mean C) Mode and geometric mean D) Mean and median E) Mean, median and geometric mean

188)

Which measures of central tendency are not affected by extremely low or extremely high values? A) Mean and median B) Mean and mode C) Mode and median D) Geometric mean and mean E) Mean only

189)

What must be the least scale of measurement for the median? A) Nominal B) Ordinal C) Interval D) Ratio

190)

What are half of the observations always greater than? A) Median B) Mode C) Mean D) Geometric mean E) Weighted mean

191)

If a frequency distribution has open-ended intervals at the extremes, which measure of central tendency is the most difficult to estimate? A) Median B) Mode C) Mean D) Mean, Median and Mode

192)

In the calculation of the arithmetic mean for grouped data, which value is used to represent all the values in a particular class? A) The upper limit of the class B) The lower limit of the class C) The frequency of the class D) The cumulative frequency preceding the class E) The midpoint of the class

193)

A disadvantage of using an arithmetic mean to summarize a set of data is A) The arithmetic mean sometimes has two values. B) It can be used for interval and ratio data C) It is always different from the median. D) It can be biased by one or two extremely small or large values. E) It doesn't always exist.

194)

The mean, as a measure of central tendency, would be inappropriate for which one of the following? A) Ages of adults at a senior citizen center B) Incomes of lawyers C) Number of pages in textbooks on statistics D) Marital status of college students at a particular university E) Number of family pets

195)

If a major sports star were to move into your neighbourhood, what would you expect to happen to the neighbourhood's "average" income? A) The mean income would increase significantly B) The median income would increase significantly C) The modal income would increase significantly D) The mean income would increase significantly, but the modal income and median income would decrease E) The standard deviation of the neighbourhood's income would get smaller

196)

The mean, as a measure of central location would be inappropriate for which one of the following? A) Ages of adults at a senior citizen center B) Incomes of lawyers C) Number of pages in textbooks on statistics D) Marital status of college students at a particular university

197)

A disadvantage of using an arithmetic mean to summarize a set of data is A) It can be used for ratio data. B) It is always different from the median. C) It can be biased by one or two extremely small or large values. D) The arithmetic mean sometimes has two values.

198)

What is a disadvantage of the range as a measure of dispersion? A) Based on only two observations B) Can be distorted by a large mean C) Not in the same units as the original data D) Has no disadvantage

199)

If a major sports star were to move into your neighbourhood, what would you expect to happen to the neighbourhood's "average" income? A) The mean income would decrease significantly B) The median income would increase significantly C) The modal income would increase significantly D) The mean income would increase significantly, but the median income would stay almost the same as before E) The standard deviation of the neighbourhood's income would get smaller

200)

The following printout is a summary of housing prices in Edmonton: Descriptive statistics List Price count

mean

447,403.14

sample variance

20,560,909,990.86

sample standard deviation

143,390.76

minimum

269,900

maximum

1,100,000

range

830,100

1 quartile

357,250.00

median

402,400.00

3 quartile

479,150.00

interquartile range

121,900.00

mode

399,900.00

What can we determine from this printout? A) The mean list price is less than both the median and modal prices B) The median list price is the most representative as it is larger than the modal price and smaller than the mean price. C) The modal price is affected by a few houses that must be priced very high D) More than half of the houses are listed above $425,000.

201)

The following printout is a summary of number of bedrooms in homes for sale in Regina: Descriptive statistics No of Bedrooms Count

mean

3.73

sample variance

1.12

sample standard deviation

1.06

minimum

maximum

range

skewness

0.04

kurtosis

2.11

coefficient of variation(CV)

28.38%

1 quartile

3.00

median

4.00

3 quartile

4.00

interquartile range

1.00

mode

4.00

What can we determine from this printout? A) The mean number of bedrooms is less than both the median and modal number. B) The median number of bedrooms is the most representative as it is larger than the modal number and smaller than the mean number of bedrooms. C) The modal number of bedrooms is affected by a few houses that must have a large number of bedrooms. D) 75% of the houses have more than 3 bedrooms.

202)

i. The sum of the deviations from the mean for the set of numbers 4, 9 and 5 will equal zero. ii. If there is an even number of ungrouped values, the median is found by arranging them from low to high and then determining the arithmetic mean of the two middle values. iii. For salaries of $102,000, $98,000, $35,000, $106,000 and $101,000, the arithmetic mean would be an appropriate average. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

203)

i. In a negatively skewed distribution, the mean is always greater than the median. ii. In a negatively skewed distribution, the median occurs at the peak of the curve. iii. In a positively skewed distribution, the mode is greater than the median. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

204)

i. In a positively skewed distribution, the mean is always greater than the median. ii. In a negatively skewed distribution, the median occurs at the peak of the curve. iii. In a negatively skewed distribution, the mode is greater than the median. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

205)

i. The mode is the value of the observation that appears most frequently. ii. A distribution that has the same shape on either side of the center is said to be symmetrical. iii. Negatively skewed indicates that a distribution is not symmetrical. The long tail is to the left or in the negative direction. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

206)

i. In a positively skewed distribution, the mean is always greater than the median. ii. In a negatively skewed distribution, the mode occurs at the peak of the curve. iii. In a negatively skewed distribution, the mode is greater than the median. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

207)

208)

What is the relationship among the mean, median and mode in a symmetric distribution? A) All values are equal B) Mean is always the smallest value C) Mean is always the largest value D) Mode is the largest value E) Median is always the largest value

Rank the measures of dispersion in terms of their relative computational difficulty from least to most difficulty. A) Mode, median, mean B) Range, mean deviation, variance C) Variance, mean deviation, range D) There is no difference

209)

The ages of a sample of telephones used in a small town hotel were organized into the following table: Ages (in years)

Number

2 to under 5

5 to under 8

8 to under 11

11 to under 14

14 to under 17

What is the sample variance? A) About 10.2 B) About 6.1 C) About 14.0 D) About 3.2 E) About 5.0

210)

A purchasing agent for a trucking company is shopping for replacement tires for their trucks from two suppliers. The suppliers' prices are the same. However, Supplier A's tires have an average life of 100,000 km with a standard deviation of 10,000 km. Supplier B's tires have an average life of 100,000 km with a standard deviation of 2,000 km. Which of the following statements is true? A) The two distributions of tire life are the same B) On average, Supplier A's tires have a longer life then Supplier B's tires C) The life of Supplier B's tire is more predictable than the life of Supplier A's tires D) The dispersion of Supplier A's tire life is less than the dispersion of Supplier B's tire life E) The life of Supplier A's tire is more predictable than the life of Supplier B's tires

211)

The sum of the differences between sample observations and the sample mean is A) Zero B) The mean deviation C) The range D) The standard deviation E) The mean

212)

Which of the following measures of dispersion are based on deviations from the mean? A) Variance B) Standard deviation C) Mean deviation D) Mean deviation, standard deviation, and variance

213)

What is the relationship between the variance and the standard deviation? A) Variance is the square root of the standard deviation B) Variance is the square of the standard deviation C) Variance is twice the standard deviation D) No constant relationship between the variance and the standard deviation

214)

What is the range for this sample of March electric bills amounts for all-electric homes of similar sizes (to the nearest dollar): $212, $191, $176, $129, $106, $92, $108, $109, $103, $121, $175, and $194. A) $100 B) $130 C) $120 D) $112 E) $115

215)

A survey of passengers on domestic flights revealed these distances: Kilometres Flown

Number of Passengers

100 to under 500

500 to under 900

900 to under 1300

1300 to under 1700

1700 to under 2100

2100 to under 2500

What is the range (in kms)? A) 2499 B) 1100 C) 2400 D) 1999 E) 2500

216)

Which measure of dispersion disregards the algebraic signs (plus and minus) of each difference between X and the mean? A) Standard deviation B) Mean deviation C) Arithmetic mean D) Variance

217)

A population consists of all the weights of all defensive tackles on Sociable University's football team. They are: Johnson, 204 pounds; Patrick, 215 pounds; Junior, 207 pounds; Kendron, 212 pounds; Nicko, 214 pounds; and Cochran, 208 pounds. What is the population standard deviation (in pounds)? A) About 4 B) About 16 C) About 100 D) About 40 E) Zero

218)

The weights (in grams) of the contents of several small bottles are 4, 2, 5, 4, 5, 2 and 6. What is the sample variance? A) 6.92 B) 4.80 C) 1.96 D) 2.33 E) Zero

219)

Each person who applies for an assembly job at Robert's Electronics is given a mechanical aptitude test. One part of the test involves assembling a plug-in unit based on numbered instructions. A sample of the length of time it took 42 persons to assemble the unit was organized into the following frequency distribution. Length of Time (in minutes )

Number

1 to under 4

4 to under 7

7 to under 10

10 to under 13

13 to under 16

16 to under 19

What is the standard deviation (in minutes)? A) 3.89 B) 6.01 C) 8.78 D) 17.00 E) Zero

220)

The following are the weekly amounts of welfare payments made by the federal government to a sample of six families: $139, $136, $130, $136, $147 and $136. What is the range? A) $0 B) $14 C) $52 D) $17 E) $147

221)

Measures of dispersion calculated from grouped data are A) Estimates B) Biased C) Means D) Skewed

222)

The closing prices of a common stock have been 61.5, 62, 61.25, 60.875 and 61.5 for the past week. What is the range? A) $1.250 B) $1.750 C) $1.125 D) $1.875

223)

Ten experts rated a newly developed chocolate chip cookie on a scale of 1 to 50. Their ratings were: 34, 35, 41, 28, 26, 29, 32, 36, 38 and 40. What is the mean deviation? A) 8.00 B) 4.12 C) 12.67 D) 0.75

224)

The weights (in kilograms) of a group of crates being shipped to Panama are 95, 103, 110, 104, 105, 112 and 92. What is the mean deviation? A) 5.43 kg B) 6.25 kg C) 0.53 kg D) 52.50 kg

225)

The ages of all the patients in the isolation ward of the hospital are 38, 26, 13, 41 and 22. What is the population variance? A) 106.8 B) 91.4 C) 240.3 D) 42.4

226)

A sample of the daily number of passengers per bus riding the Bee Line commuter route yielded the following information: Number of Passengers

Frequency

0 to under 5

5 to under 10

10 to under 15

15 to under 20

20 to under 25

What is the standard deviation? A) About 6.06 B) About 20.0 C) About 12.9 D) About 2.3

227)

i. The standard deviation is the positive square root of the variance. ii. For a symmetrical distribution, the variance is equal to the standard deviation. iii. If the standard deviation of the ages of a female group of employees is six years and the standard deviation of the ages of a male group in the same plant is ten years, it indicates that there is more spread in the ages of the female employees. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements

228)

i. If a frequency distribution is open-ended, the variance cannot be determined. ii. The range cannot be computed for data grouped in a frequency distribution having an open end. iii. The standard deviation is the positive square root of the variance A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements

229)

What disadvantage(s) are there of the mean deviation? A) Based on only two observations B) Based on deviations from the mean C) Uses absolute values, which are difficult to manipulate

230)

A sample of the monthly amounts spent for food by families of four receiving food stamps approximates a symmetrical distribution. The sample mean is $150 and the standard deviation is $20. Using the Empirical Rule, about 95 percent of the monthly food expenditures are between what two amounts? A) $100 and $200 B) $85 and $105 C) $205 and $220 D) $110 and $190

231)

A sample of assistant professors on the business faculty at the largest college in Ontario revealed the mean annual income to be $62,000 with a standard deviation of $3,000. Using the Empirical Rule, what proportion of faculty earn more than $56,000 but less than $68,000? A) At least 50% B) Approximately 68% C) At least 75% D) Approximately 95% E) Almost all

232)

Samples of the wires coming off the production line were tested for tensile strength. The statistical results (in PSI) were: Arithmetic mean

500

Median

500

Mode

500

Standard deviation

Mean deviation

Quartile deviation

Range

240

Number in sample

100

According to the Empirical Rule, the middle 95 percent of the wires tested between approximately what two values? A) 450 and 550 B) 460 and 540 C) 420 and 580 D) 380 and 620

233)

The distribution of a sample of the outside diameters of PVC gas pipes approximates a symmetrical, bell-shaped distribution. The arithmetic mean is 14.0 cm, and the standard deviation is 0.1 cm. About 68 percent of the outside diameters lie between what two amounts? A) 13.5 and 14.5 cm B) 13.0 and 15.0 cm C) 13.9 and 14.1 cm D) 13.8 and 14.2 cm

234)

Below is a summary of the size of homes for sale in Regina in 2005. The Empirical Rule would suggest that the middle 68% of the home sizes are between what two approximate values? Size

A) B) C) D)

(sq ft )

count

mean

1,713.38

sample variance

674,283.32

sample standard deviation

821.15

minimum

maximum

4737

range

4737

1,000 to 2,000 sq. ft. 892 to 2,534 sq ft. 71 to 3,355 sq ft. 0 to 4,176 sq ft.

235)

Below is a summary of the size of homes for sale in Regina in 2005. The Empirical Rule would suggest that the middle 95% of the home sizes are between what two approximate values? Size

A) B) C) D)

(sq ft )

count

mean

1,713.38

sample variance

674,283.32

sample standard deviation

821.15

minimum

maximum

4737

range

4737

1,000 to 2,000 sq. ft. 892 to 2,534 sq ft. 71 to 3,355 sq ft. 0 to 4,176 sq ft.

236)

The Empirical Rule states that:

(i) about 68% of the observation will lie within one standard deviation of the mean. ii. about 95% of the observations will lie within two standard deviations of the mean. iii. and virtually all (99.7%) will lie within three standard deviations of the mean. A) (i), (ii) and (iii) are all correct statements. B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

237)

Chebyshev's theorem states that:

i. About 68% of the observation will lie within one standard deviation of the mean. ii. About 95% of the observations will lie within two standard deviations of the mean. iii. Virtually all (99.7%) will lie within three standard deviations of the mean. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

238)

i. An outlier is a value in a data set that is inconsistent with the rest of the data. ii. The interquartile range is the difference between the values of the first and third quartile, indicating the range of the middle fifty percent of the observations. iii. A percentile divides a distribution into one hundred equal parts. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

239)

i. An outlier is a value in a data set that is inconsistent with the rest of the data. ii. The interquartile range is the difference between the values of the first and third quartile, indicating the range of the middle fifty percent of the observations. iii. A student scored in the 85 percentile on a standardized test. This means that the student scored lower than 85% of the rest of the students taking the test. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

240)

i. A percentile divides a distribution into one hundred equal parts. ii. A student scored in the 85 percentile on a standardized test. This means that the student scored lower than 85% of the rest of the students taking the test. iii. The interquartile range is the difference between the values of the first and third quartile, indicating the range of the middle fifty percent of the observations. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) is a correct statement, but not (ii) or (iii). E) (i), (ii) and (iii) are all false statements.

241)

i. A percentile divides a distribution into one hundred equal parts. ii. A student scored in the 85 percentile on a standardized test. This means that the student scored higher than 85% of the rest of the students taking the test. iii. The interquartile range is the difference between the values of the first and third quartile, indicating the range of the middle fifty percent of the observations. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

242)

What do the quartile deviation and the interquartile range describe? A) Lower 50% of the observations B) Middle 50% of the observations C) Upper 50% of the observations D) Lower 25% and the upper 25% of the observations

243)

i. An outlier is a data point that always occurs in the first quartile. ii. A student scored in the 85 percentile on a standardized test. This means that the student scored higher than 85% of the rest of the students taking the test. iii. The interquartile range is the difference between the values of the first and third quartile, indicating the range of the middle fifty percent of the observations. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

244)

i. The interquartile range is the average of the values of the first and third quartile. ii. An outlier is a data point that always occurs in the first quartile. iii. A student scored in the 85 percentile on a standardized test. This means that the student scored lower than 85% of the rest of the students taking the test. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

245)

A box plot shows A) The mean and variance B) The relative symmetry of a distribution for a set of data C) The percentiles of a distribution D) The deciles of a distribution E) The location of the mean of a distribution

246)

What statistics are needed to draw a box plot? A) Minimum, maximum, median, first and third quartiles B) Median, mean and standard deviation C) A mean and dispersion D) A mean and a standard deviation E) Q1, Q2 and Q3

247)

The coefficient of variation for a set of annual incomes is 18%; the coefficient of variation for the length of service with the company is 29%. What does this indicate? A) More dispersion in the distribution of the incomes compared with the dispersion of their length of service B) More dispersion in the lengths of service compared with incomes C) Dispersion in the two distributions (income and service) cannot be compared using percents D) Dispersions are equal

248)

Mr. and Mrs. Jones live in a neighbourhood where the mean family income is $45,000 with a standard deviation of $9,000. Mr. and Mrs. Smith live in a neighbourhood where the mean is $100,000 and the standard deviation is $30,000. What are the relative dispersions of the family incomes in the two neighbourhoods? A) Jones 40%, Smith 20% B) Jones 20%, Smith 30% C) Jones 30%, Smith 20% D) Jones 50%, Smith 33%

249)

A large oil company is studying the number of gallons of gasoline purchased per customer at self-service pumps. The mean number of litres is 10.0 with a standard deviation of 3.0 litres. The median is 10.75 litres. What is the Pearson's coefficient of skewness? A) - 1.00 B) - 0.75 C) + 0.75 D) + 1.00

250)

What is the value of the Pearson coefficient of skewness for a distribution with a mean of 17, median of 12 and standard deviation of 6? A) + 2.5 B) - 2.5 C) + 0.83 D) - 0.83

251)

A study of business faculty in Ontario revealed that the arithmetic mean annual salary is $62,000 and a standard deviation of $3,000. The study also showed that the faculty had been employed an average (arithmetic mean) of 15 years with a standard deviation of 4 years. How does the relative dispersion in the distribution of salaries compare with that of the lengths of service? A) Salaries about 100%, service about 50% B) Salaries about 5%, service about 27% C) Salaries about 42%, service about 81% D) Salaries about 2%, service about 6%

252)

The printout below is a summary of the average annual earnings of male full time workers in Canada from 1999-2008. Determine the coefficient of variation. Men

A) B) C) D) E)

1.0% 2.1% 3% 15% 25%

count

mean

44,700.00

sample variance

1,011,111.11

sample standard deviation

1,005.54

minimum

43000

maximum

46900

range

3900

population variance

910,000.00

population standard deviation

953.94

253)

The printout below is a summary of the average annual earnings of male full time workers in Canada from 1999-2008. Determine the coefficient of variation. Women ’s Earnings 1999-2008

A) B) C) D) E)

254)

255)

count

mean

28,320.00

sample variance

1,152,888.89

sample standard deviation

1,073.73

minimum

27000

maximum

30200

range

3200

1.0% 2.5% 3% 3.8% 4.25%

The coefficient of variation generally lies between what two values? A) - 1 and + 1 B) - 3 and + 3 C) 0% and 100% D) Unlimited values

A research analyst wants to compare the dispersion in the price-earnings ratios for a group of common stock with their return on investment. For the price-earnings ratios, the mean is 10.9 and the standard deviation is 1.8. The mean return on investment is 25 percent and the standard deviation 5.2 percent. What is the relative dispersion for the price-earnings ratios and return on investment? A) Ratios = 32.0 percent, investment = 19.0 percent B) Ratios = 16.5 percent, investment = 20.8 percent C) Ratios = 132.0 percent, investment = 190.0 percent D) Ratios = 50.0 percent, investment = 10.0 percent

256)

A study of the scores on an in-plant course in management principles and the years of service of the employees enrolled in the course resulted in these statistics: i. Mean test score was 200 with a standard deviation of 40 ii. Mean number of years of service was 20 years with a standard deviation of 2 years. In comparing the relative dispersion of the two distributions, what are the coefficients of variation? A) Test 50%, service 60% B) Test 100%, service 400% C) Test 20%, service 10% D) Test 35%, service 45%

257)

A large group of inductees was given a mechanical aptitude and a finger dexterity test. The arithmetic mean score on the mechanical aptitude test was 200, with a standard deviation of 10. The mean and standard deviation for the finger dexterity test were 30 and 6 respectively. What is the relative dispersion in the two groups? A) Mechanical 5 percent, finger 20 percent B) Mechanical 20 percent, finger 10 percent C) Mechanical 500 percent, finger 200 percent D) Mechanical 50 percent, finger 200 percent

258)

A study of business faculty in Ontario revealed that the arithmetic mean annual salary is $72,000 and a standard deviation of $3,000. The study also showed that the faculty had been employed an average (arithmetic mean) of 15 years with a standard deviation of 4 years. How does the relative dispersion in the distribution of salaries compare with that of the lengths of service? A) Salaries about 100%, service about 50% B) Salaries about 4%, service about 27% C) Salaries about 42%, service about 81% D) Salaries about 2%, service about 6%

259)

In order to predict life expectancy, a data sample is received from a local funeral parlour. The sample includes the ages (in years) of each of the customers received over the past few weeks. The following is the Excel summary statistics: Mean

64.9

Standard Error

1.67

Median

69.1

Mode

73.7

Standard Deviation

10.6

Sample Variance

111.8

Kurtosis

-0.2

Skewness

-1.0

Range

37.3

Minimum

39.5

Maximum

76.8

Sum

2595.9

Count

Largest(2)

76.1

Smallest(2)

44.9

259.1) What is the size of the sample? A) 40 B) 46 C) 44.9 D) 2595.9

259.2) Determine the age of the youngest person who died in this sample. A) 76.1 B) 39.5 C) 44.9 D) 76.8

259.3) Determine the age of the oldest person who died in this sample. A) 37.3 B) 39.5 C) 44.9 D) 76.8

259.4) Describe the shape of the age of death distribution. A) Slight positive skewness B) Slight negative skewness C) Perfectly symmetrical D) You cannot determine this from the data given E) Strong negative skewness

259.5) Describe the shape of the age of death distribution.

(i) Since the mode is the largest of the 3 measures of central tendency, more people died at this older age than any earlier age (ii) Since the mean age of death is the lowest of the three measures of central tendency, there must have been one or more person who died at a significantly younger age than the mode (iii) Since the mode is the largest of the 3 measures of central tendency, everyone died at this age A) (i) and (ii) are correct statements, but (iii) is false. B) (ii) and (iii) are correct statements, but (i) is false. C) (i), (ii) and (iii) are all correct statements. D) (i) and (iii) are correct statements, but (ii) is false. E) (i), (ii) and (iii) are all false statements.

260)

(i) The mean is the measure of central tendency that uses all of the observations in its calculation. (ii) The mode is the class with the largest number of observations. (iii) If a set of observations contains an extreme value and none of the observations repeat themselves, the median is the most representative measure of central tendency. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

261)

(i) The mean is the measure of central tendency that uses all of the observations in its calculation. (ii) The mode is the class with the fewest number of observations. (iii) If a set of observations contains an extreme value and none of the observations repeat themselves, the median is the most representative measure of central tendency. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

262)

(i) The mean is the measure of central tendency that uses all of the observations in its calculation. (ii) The mode is the class with the largest number of observations. (iii) If a set of observations contains an extreme value and none of the observations repeat themselves, the mean is the most representative measure of central tendency. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

263)

(i) The median is the measure of central tendency that uses all of the observations in its calculation. (ii) The mode is the class with the largest number of observations. (iii) If a set of observations contains an extreme value and none of the observations repeat themselves, the median is the most representative measure of central tendency. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

264)

(i) The weekly sales from a sample of ten computer stores yielded a mean of $25,900; a median $25,000 and a mode of $24,500. The shape of the distribution is positively skewed (ii) For the median (measure of central tendency), the data must be ranked before it is possible to determine it. (iii) If the sum of all the values of a distribution is divided by the number of values, the result is the arithmetic mean. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

265)

(i) The weekly sales from a sample of ten computer stores yielded a mean of $25,900; a median $25,000 and a mode of $24,500. The shape of the distribution is negatively skewed (ii) For the median (measure of central tendency), the data must be ranked before it is possible to determine it. (iii) If the sum of all the values of a distribution is divided by the number of values, the result is the arithmetic mean. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

266)

(i) The weekly sales from a sample of ten computer stores yielded a mean of $25,900; a median $25,000 and a mode of $24,500. The shape of the distribution is positively skewed (ii) For the mean (measure of central tendency), the data must be ranked before it is possible to determine it. (iii) If the sum of all the values of a distribution is divided by the number of values, the result is the arithmetic mean. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

267)

(i) If a distribution is highly skewed, the mean (measure of central tendency) should be avoided. (ii) A characteristic of the population is called a parameter (iii) A sample revealed that the ages of musicians playing in small local combos are 36, 29, 37, 32, 36 and 75. The median is the most appropriate measure of central tendency to represent the ages of the musicians. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

268)

(i) If a distribution is highly skewed, the median (measure of central tendency) should be avoided. (ii) A characteristic of the population is called a parameter (iii) A sample revealed that the ages of musicians playing in small local combos are 36, 29, 37, 32, 36 and 75. The median is the most appropriate measure of central tendency to represent the ages of the musicians. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

269)

(i) If a distribution is highly skewed, the mean (measure of central tendency) should be avoided. (ii) A characteristic of the population is called a statistic. (iii) A sample revealed that the ages of musicians playing in small local combos are 36, 29, 37, 32, 36 and 75. The median is the most appropriate measure of central tendency to represent the ages of the musicians. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

270)

(i) The arithmetic mean (measure of central tendency) cannot be determined if the distribution has an open-ended class. (ii) The measure of central tendency used to determine the average annual percent increase in sales from one time period to another is the geometric mean. (iii) The smallest measure of central tendency in a positively skewed distribution is the mode. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

271)

(i) The median (measure of central tendency) cannot be determined if the distribution has an open-ended class. (ii) The measure of central tendency used to determine the average annual percent increase in sales from one time period to another is the geometric mean. (iii) The smallest measure of central tendency in a positively skewed distribution is the mode A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

272)

(i) The arithmetic mean (measure of central tendency) cannot be determined if the distribution has an open-ended class. (ii) The measure of central tendency used to determine the average annual percent increase in sales from one time period to another is the arithmetic mean. (iii) The smallest measure of central tendency in a positively skewed distribution is the mode A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

273)

(i) A small manufacturing company with 52 employees has annual salaries distributed such that the mean is $25,459, the median is $24,798 and the mode is $24,000. An additional foreman is hired at an annual salary of $50,700. The measure of central tendency that is most affected by the addition of this salary is the arithmetic mean. (ii) In the relationship between the mean and median in a negatively skewed distribution the mean is less than the median. (iii) In the relationship between the median and the mode in a positively skewed distribution, the median is greater than the mode. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

274)

(i) A small manufacturing company with 52 employees has annual salaries distributed such that the mean is $25,459, the median is $24,798 and the mode is $24,000. An additional foreman is hired at an annual salary of $50,700. The measure of central tendency that is most affected by the addition of this salary is the arithmetic mean. (ii) In the relationship between the mean and median in a negatively skewed distribution the mean is less than the median. (iii) In the relationship between the median and the mode in a positively skewed distribution, the median is smaller than the mode. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

275)

(i) A small manufacturing company with 52 employees has annual salaries distributed such that the mean is $25,459, the median is $24,798 and the mode is $24,000. An additional foreman is hired at an annual salary of $50,700. The measure of central tendency that is most affected by the addition of this salary is the median. (ii) In the relationship between the mean and median in a negatively skewed distribution the mean is less than the median. (iii) In the relationship between the median and the mode in a positively skewed distribution, the median is greater than the mode. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

276)

(i) Five students were given a page of problems with the instructions to solve as many as they could in one hour. Five students solved the following number of problems: 12, 10, 8, 6 and 4. The arithmetic mean number of minutes required per problem is 7.5 minutes (average of 8 problems in an hour). (ii) David Electronics had a profit of $10 million in 1998. Profit doubled from 1998 to 1999 and profit increased eight fold from 1999 to 2000. The annual geometric mean rate of growth from 1998 to 2000 was 300% (4 fold). (iii) The difference between the highest and the lowest value in a set of data is called the range. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

277)

(i) Five students were given a page of problems with the instructions to solve as many as they could in one hour. Five students solved the following number of problems: 12, 10, 8, 6 and 4. The arithmetic mean number of minutes required per problem is 7.5 minutes (average of 8 problems in an hour). (ii) David Electronics had a profit of $10 million in 1998. Profit doubled from 1998 to 1999 and profit increased eight fold from 1999 to 2000. The annual geometric mean rate of growth from 1998 to 2000 was 200% (3 fold). (iii) The difference between the highest and the lowest value in a set of data is called the range. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

278)

(i) Five students were given a page of problems with the instructions to solve as many as they could in one hour. Five students solved the following number of problems: 12, 10, 8, 6 and 4. The arithmetic mean number of minutes required per problem is 6.5 minutes (average of 7 problems in an hour). (ii) David Electronics had a profit of $10 million in 1998. Profit doubled from 1998 to 1999 and profit increased eight fold from 1999 to 2000. The annual geometric mean rate of growth from 1998 to 2000 was 300% (4 fold). (iii) The difference between the highest and the lowest value in a set of data is called the range. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

279)

(i) If the mean of a frequency distribution is smaller than the median and mode, the Pearson's coefficient of skewness would be negative. (ii) The only time the variance equals the standard deviation is when both equal 1. (iii) According to the Empirical Rule, 68 percent of the observations lie within plus and minus one standard deviation of the mean. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

280)

(i) If the mean of a frequency distribution is smaller than the median and mode, the Pearson's coefficient of skewness would be positive. (ii) The only time the variance equals the standard deviation is when both equal 1. (iii) According to the Empirical Rule, 90 percent of the observations lie within plus and minus one standard deviation of the mean. A) Only (ii) is correct. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

281)

(i) If the mean of a frequency distribution is smaller than the median and mode, the Pearson's coefficient of skewness would be negative. (ii) The only time the variance equals the standard deviation is when both equal 1. (iii) According to the Empirical Rule, 99 percent of the observations lie within plus and minus one standard deviation of the mean. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

282)

(i) The standard deviation the positive square root of the variance. (ii) The capacities of several metal containers are: 38, 20, 37, 64, and 27 litres. The range in litres is 44. (iii) The sum of the deviations of each value from the mean equals zero. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

283)

(i) The standard deviation is the negative square root of the variance. (ii) The capacities of several metal containers are: 38, 20, 37, 64, and 27 litres. The range in litres is 44. (iii) The sum of the deviations of each value from the mean equals zero. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

284)

(i) The standard deviation the positive square root of the variance. (ii) The capacities of several metal containers are: 38, 20, 37, 64, and 27 litres. The range in litres is 24. (iii) The sum of the deviations of each value from the mean equals zero. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

285)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A study is made of the commissions paid to furniture salespersons. If the variance is computed, it would be measured in dollars squared. (iii) The coefficient of variation is a measure of relative dispersion. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

286)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A study is made of the commissions paid to furniture salespersons. If the variance is computed, it would be measured in dollars squared. (iii) The coefficient of skewness is a measure of relative dispersion. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

287)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A study is made of the commissions paid to furniture salespersons. If the standard deviation is computed, it would be measured in dollars squared. (iii) The coefficient of variation is a measure of relative dispersion. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

288)

(i) The research director of a large oil company conducted a study of the buying habits of consumers with respect to the amount of gasoline purchased at full-service pumps. The arithmetic mean amount is 11.5 litres and the median amount is 11.95 litres. The standard deviation of the sample is 4.5 litres. The Pearson's coefficient of skewness can be calculated to be -0.30. (ii) Rainbow Trout, Inc., feeds fingerling trout in special ponds and markets them when they attain a certain weight. A group of 9 trout (considered the population) were isolated in a pond and fed a special food mixture called Grow Em Fast. At the end of the experimental period, the weights of the trout were (in grams): 124, 125, 123, 120, 124, 127, 125, 126 and 121. Another special mixture, Fatso 1B, was used in another pond. The mean of the population was computed to be 126.9 grams and the standard deviation was 1.20 grams. When these data are analyzed, we discover that the food resulting in a more uniform weight is Fatso 1B. (iii) A study has been made of the number of hours a light bulb will operate before it burns out. If the variance of this distribution were computed, it would be measured in hours squared A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

289)

(i) The research director of a large oil company conducted a study of the buying habits of consumers with respect to the amount of gasoline purchased at full-service pumps. The arithmetic mean amount is 11.5 gallons and the median amount is 11.95 litres. The standard deviation of the sample is 4.5 litres. The Pearson's coefficient of skewness can be calculated to be + 0.30. (ii) Rainbow Trout, Inc., feeds fingerling trout in special ponds and markets them when they attain a certain weight. A group of 9 trout (considered the population) were isolated in a pond and fed a special food mixture called Grow Em Fast. At the end of the experimental period, the weights of the trout were (in grams): 124, 125, 123, 120, 124, 127, 125, 126 and 121. Another special mixture, Fatso 1B, was used in another pond. The mean of the population was computed to be 126.9 grams and the standard deviation was 1.20 grams. When these data are analysed, we discover that the food resulting in a more uniform weight is Fatso 1B. (iii) A study has been made of the number of hours a light bulb will operate before it burns out. If the variance of this distribution were computed, it would be measured in hours squared A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

290)

The annual incomes of the five vice presidents of Elly's Industries are: $41,000, $38,000, $32,000, $33,000 and $50,000. The annual incomes of Unique, another firm similar to Elly's Industries, were also studied and found to have a mean of $38,900 and a standard deviation of $6,612. Which firm has the greater coefficient of variation? A) Elly's Industries B) Unique C) Both firms have the same coefficient of variation D) We have not been given sufficient information to determine.

291)

The annual incomes of the five vice presidents of Elly's Industries are: $41,000, $38,000, $32,000, $33,000 and $50,000. The annual incomes of Unique, another firm similar to Elly's Industries, were also studied and found to have a mean of $38,900 and a standard deviation of $6,612. Determine the coefficient of variation for each firm. A) Elly's Industries = 17, Unique = 19 B) Elly's Industries = 17, Unique = 17 C) Elly's Industries = 16, Unique = 18 D) Elly's Industries = 18, Unique = 17

292)

The lengths of stay on the cancer floor of Community Hospital were organized into a frequency distribution. The mean length was 28 days, the median 25 days and the modal length 23 days. The standard deviation was computed to be 4.2 days. Determine the Pearson's coefficient of skewness. A) 2.41 B) -2.41 C) 2.14 D) -2.14

293)

(i) The research director of a large oil company conducted a study of the buying habits of consumers with respect to the amount of gasoline purchased at full-service pumps. The arithmetic mean amount is 11.5 litres and the median amount is 11.95 litres. The standard deviation of the sample is 4.5 litres. The Pearson's coefficient of skewness can be calculated to be -0.30. (ii) Rainbow Trout, Inc., feeds fingerling trout in special ponds and markets them when they attain a certain weight. A group of 9 trout (considered the population) were isolated in a pond and fed a special food mixture called Grow Em Fast. At the end of the experimental period, the weights of the trout were (in grams): 124, 125, 123, 120, 124, 127, 125, 126 and 121. Another special mixture, Fatso 1B, was used in another pond. The mean of the population was computed to be 126.9 grams and the standard deviation was 1.20 grams. When these data are analyzed, we discover that the food resulting in a more uniform weight is Fatso 1B. (iii) A study has been made of the number of hours a light bulb will operate before it burns out. If the standard deviation of this distribution were computed, it would be measured in hours squared A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

294)

(i) The research director of a large oil company conducted a study of the buying habits of consumers with respect to the amount of gasoline purchased at full-service pumps. The arithmetic mean amount is 11.5 litres and the median amount is 11.95 litres. The standard deviation of the sample is 4.5 litres. The Pearson's coefficient of skewness can be calculated to be -0.30. (ii) Rainbow Trout, Inc., feeds fingerling trout in special ponds and markets them when they attain a certain weight. A group of 9 trout (considered the population) were isolated in a pond and fed a special food mixture called Grow Em Fast. At the end of the experimental period, the weights of the trout were (in grams): 124, 125, 123, 120, 124, 127, 125, 126 and 121. Another special mixture, Fatso 1B, was used in another pond. The mean of the population was computed to be 126.9 grams and the standard deviation was 5.20 grams. When these data are analysed, we discover that the food resulting in a more uniform weight is Fatso 1B. (iii) A study has been made of the number of hours a light bulb will operate before it burns out. If the variance of this distribution were computed, it would be measured in hours squared A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

295)

(i) The research director of a large oil company conducted a study of the buying habits of consumers with respect to the amount of gasoline purchased at full-service pumps. The arithmetic mean amount is 11.5 litres and the median amount is 11.95 litres. The standard deviation of the sample is 4.5 litres. The Pearson's coefficient of skewness can be calculated to be -0.30. (ii) The Pearson's coefficient of skewness (Sk) measures the amount of skewness and may range from -3.0 to + 3.0. It is computed by subtracting the median from the mean, multiplying the result by 3 and dividing by standard deviation. (iii) A study has been made of the number of hours a light bulb will operate before it burns out. If the variance of this distribution were computed, it would be measured in hours squared A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

296)

A company's human resource department was interested in the average number of years that a person works before retiring. The sample of size 11 follows: 12

296.1) (i) The mode is 21.

(ii) The arithmetic mean is 20.4. (iii) The median is 21. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

296.2) (i) The mode is 3.

296.3) (i) The mode is 21.

(ii) The arithmetic mean is 20.4. (iii) The median is 23. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

296.4) (i) Based on the values of the arithmetic mean, median, and mode, the distribution is most

likely symmetrical. (ii) The arithmetic mean is 20.4. (iii) The median is 21. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297)

A sample of five flooring installers, each carrying three types of flooring, was taken and the price per square metre (to the nearest cent) was recorded for each type of flooring, as shown in the table below. INSTALLER Flooring Type

Laminate Floor

$1.27

Polyester Carpet

.36

1.37

1.38

1.40

Nylon Carpet

1.47

1.49

1.50

1.59

297.1) (i) The range for laminate flooring is 0 or none.

(ii) The range for polyester carpet is $0.04 or 4 cents. (iii) The mean deviation for laminate flooring is 0. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.2) (i) The range for laminate flooring is 0 or none.

(ii) The mean deviation for laminate flooring is 0. (iii) The range for nylon carpet is $0.12 or 12 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.3) (i) The range for laminate flooring is 0 or none.

(ii) The variance for laminate flooring is 0. (iii) The range for nylon carpet is $0.12 or 12 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.4) (i) The range for laminate flooring is 0 or none.

(ii) The variance for laminate flooring is 1. (iii) The range for nylon carpet is $0.12 or 12 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.5) (i) The range for laminate flooring is 0 or none.

(ii) The variance for laminate flooring is 0. (iii) The range for nylon carpet is $0.15 or 15 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.6) (i) The range for laminate flooring is 0 or none.

(ii) The standard deviation for nylon carpet is 4.64 cents (iii) The range for nylon carpet is $0.12 or 12 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.7) (i) The range for laminate flooring is 0 or none.

(ii) The standard deviation for nylon carpet is 4.64 cents (iii) The range for nylon carpet is $0.15 or 15 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.8) (i) The range for laminate flooring is 0 or none.

(ii) The standard deviation for nylon carpet is 6.64 cents (iii) The range for nylon carpet is $0.12 or 12 cents. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.9) (i) The range for laminate flooring is 1.

297.10) (i) The standard deviation for laminate flooring is 0.

(ii) The standard deviation for polyester carpet is $1.48. (iii) The range for polyester carpet is $1.04. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

297.11) (i) The standard deviation for laminate flooring is 0.

(ii) The standard deviation for polyester carpet is $1.88. (iii) The range for polyester carpet is $1.04. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

298)

The weights of a sample of 100 boxes being shipped by Air France from Toronto to Paris

are: Weights (kg )

Number

50 to under 75

75 to under 100

100 to under 125

125 to under 150

150 to under 175

298.1) (i) Correct to two decimal places, the sample standard deviation is approximately 25.99.

(ii) Correct to two decimal places, the sample variance is approximately 675.25. A) (i) and(ii) are correct statements B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are both false statements

298.2) (i) Correct to two decimal places, the sample standard deviation is approximately 25.99.

(ii) Correct to two decimal places, the sample variance is approximately 1475.22. A) (i) and (ii) are both correct statements B) (i) is a correct statement but not (ii). C) (ii) is correct but not (i). D) (i) and (ii) are both false statements.

298.3) (i) Correct to two decimal places, the sample standard deviation is approximately 52.98.

(ii) Correct to two decimal places, the sample variance is approximately 675.25. A) (i) and (ii) are both correct statements B) (i) and (ii) are both false statements. C) (i) is a correct statement but not (ii). D) (ii) is correct, but not (i).

299)

A telemarketing firm is monitoring the performance of its employees based on the number of sales per hour. One employee had the following sales for the last 20 hours 9

299.1) (i) The median for the distribution of number of sales per hour is 5 sales per hour.

(ii) The first quartile for the distribution of number of sales per hour is 4 sales per hour. (iii) For the distribution of number of sales per hour, 50% of the observations are between 4 and 6.25. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

299.2) (i) The median for the distribution of number of sales per hour is 6 sales per hour.

299.3) (i) The median for the distribution of number of sales per hour is 5 sales per hour.

(ii) The first quartile for the distribution of number of sales per hour is 4 sales per hour. (iii) For the distribution of number of sales per hour, 50% of the observations are between 3 and 7.5. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

300)

Calculate the Software Coefficient of Skewness for the following sample data:

5 5 7 7 7. A) 0.61 B) -0.61 C) 0 D) 2.2 E) -2.2

301)

The following printout is a summary of number of bedrooms in homes for sale in Regina: Descriptive statistics No of Bedrooms count

mean

3.73

sample variance

1.12

sample standard deviation

1.06

minimum

maximum

range

skewness

0.04

kurtosis

2.11

coefficient of variation(CV)

28.38%

1 quartile

3.00

median

4.00

3 quartile

4.00

interquartile range

1.00

mode

4.00

What can we determine from this printout? A) The mean number of bedrooms is more than both the median and modal number. B) Most of the houses have 4 bedrooms. C) The modal number of bedrooms is affected by a few houses that must have a large number of bedrooms. D) More than half of the houses have less than 3 bedrooms.

302)

i. The sum of the deviations from the mean for the set of numbers 4, 9 and 5 will equal zero. ii. If there is an even number of ungrouped values, the median is found by arranging them from low to high and then determining the arithmetic mean of the two middle values. iii. For salaries of $102,000, $98,000, $35,000, $106,000 and $101,000, the median would be an appropriate average. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

303)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A sample of the homes currently offered for sale revealed that the mean asking price is $75,900, the median $70,100 and the modal price is $67,200. The standard deviation of the distribution is $5,900. The Pearson's coefficient of skewness is 2.95 (iii) The coefficient of variation is a measure of relative dispersion. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

304)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A sample of the homes currently offered for sale revealed that the mean asking price is $75,900, the median $70,100 and the modal price is $67,200. The standard deviation of the distribution is $5,900. The Pearson's coefficient of skewness is 2.95 (iii) The coefficient of skewness is a measure of relative dispersion. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

305)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A sample of the homes currently offered for sale revealed that the mean asking price is $75,900, the median $70,100 and the modal price is $67,200. The standard deviation of the distribution is $5,900. The Pearson's coefficient of skewness is 3.95 (iii) The coefficient of variation is a measure of relative dispersion. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

306)

(i) If two sets of data are in different units, we can compare the dispersion by using coefficient of variation. (ii) A sample of the homes currently offered for sale revealed that the mean asking price is $75,900, the median $70,100 and the modal price is $67,200. The standard deviation of the distribution is $5,900. The Pearson's coefficient of skewness is 2.95 (iii) The coefficient of variation is a measure of central tendency. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

307)

(i) The research director of a large oil company conducted a study of the buying habits of consumers with respect to the amount of gasoline purchased at full-service pumps. The arithmetic mean amount is 11.5 litres and the median amount is 11.95 litres. The standard deviation of the sample is 4.5 litres. The Pearson's coefficient of skewness can be calculated to be + 0.20. (ii) The Pearson's coefficient of skewness (Sk) measures the amount of skewness and may range from -3.0 to + 3.0. It is computed by subtracting the median from the mean, multiplying the result by 3 and dividing by standard deviation. (iii) A study has been made of the number of hours a light bulb will operate before it burns out. If the variance of this distribution were computed, it would be measured in hours squared A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

308)

The information below shows the summary statistics of data adapted from Statistics Canada, regarding gasoline prices from urban cities across Canada. Average retail price for gasoline across Canada 2013 (cents per litre) Mean

123.5647

Standard Error

2.403489

Median

125.8

Mode

#N/A

Standard Deviation

9.90984

Sample Variance

98.20493

Kurtosis

-0.55113

Skewness

-0.56333

Range

33.3

Minimum

105.6

Maximum

138.9

Sum

2100.6

Count

308.1) (i) This data is based on values from 17 cities.

(ii) The average gas price in 2013 across the country based on this sample was $1.2356 (iii) More than 50% of the cities reported average gas prices over $1.258 per litre A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (ii) and (iii) are correct statements, but not (i). D) (i), (ii) and (iii) are all false statements.

308.2) (i) This data is based on values from 17 cities.

(ii) The average gas price in 2013 across the country based on this sample was $1.2356 (iii) 50% of the cities reported average gas prices over $1.23 per litre A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements, but not (i). E) (i), (ii) and (iii) are all false statements.

309)

Refer to the following distribution of the of commissions for all the companies sales force: Daily commissions

Class frequencies

$60 to under $80

80 to under 100

100 to under 120

120 to under 140

140 to under 160

160 to under 180

180 to under 200

200 to under 220

309.1) What is the population mean for the table of commissions above? A) $22.15 B) $143.40 C) $144.70 D) $160.00

309.2) What is the median for the table of commissions above? A) $22.15 B) $143.40 C) $144.67 D) $160.00

309.3) What is the range for the table of commissions above? A) $22.15 B) $143.40 C) $144.67 D) $160.00

309.4) What is the variance for the table of commissions above? A) $20.00 B) $100 C) $1008.44 D) $1018.63

309.5) What is the standard deviation for the table of commissions above? A) $20.00 B) $100 C) $22.14 D) $31.76

309.6) What is the coefficient of variation for the table of commissions above? A) 20.00% B) 20.15% C) 22.00% D) 22.15%

309.7) What is the type of skewness for the table of commissions above? A) Not available B) Symmetrical C) Positive D) Negative

309.8) What is the Pearson coefficient of skewness for the table of commissions above? A) - 0.12 B) + 0.12 C) - 0.22 D) - 0.22 E) 0

310)

Refer to the following sample of Daily covid-19 cases during the fourth wave: 727

640

653

647

310.1) Determine the mean number of daily cases. A) Not available B) 605 C) 627 D) 261

310.2) Determine the median number of daily cases. A) Not available B) 605 C) 627 D) 261

310.3) Determine the modal number of daily cases. A) Not available B) 605 C) 627 D) 261

613

466

495

597

310.4) Calculate the range in daily cases. A) Not available B) 605 C) 627 D) 261

310.5) Based on the data, what would the shape of the distribution be? A) Positively skewed B) Negatively skewed C) Symmetrical D) Not available

310.6) Calculate the number of daily cases for the 1st Quartile: Q1 A) 520.5 B) 605 C) 627 D) 261

310.7) Calculate the number of daily cases for the 3rd Quartile: Q3 A) 520.5 B) 605 C) 627 D) 651.5

310.8) Find the range in cases of the middle 50% of cases: The interquartile range A) 131 B) 261 C) 627 D) 651.5

310.9) Compute the mean deviation for the number of daily cases A) 606.6 B) 64 C) 7389 D) 86.0

310.10) Compute the variance for the number of daily cases A) 606.6 B) 64 C) 7389 D) 86.0

310.11) Compute the standard deviation for the number of daily cases A) 606.6 B) 64 C) 7389 D) 86.0

310.12) Compute the coefficient of variation for the number of daily cases A) 64.0 B) 86.0 C) 14.2 D) 7389

310.13) What is the coefficient of skewness for the number of daily cases A) Not available B) Positive C) -0.76 D) 0.76

310.14) 4/10 of the cases are below what # of daily cases: Calculate the fourth decile A) Not available B) 3.6 C) 606.6 D) 646

310.15) 65% of the cases are below what # of daily cases: Calculate the 65th percentile A) Not available B) 3.6 C) 606.6 D) 646

Answer Key Test name: chapter 3 148) B 149) Section Break 149.1) A 149.2) D 149.3) E 150) B 151) E 152) D 153) E 154) D 155) B 156) D 157) C 158) D 159) B 160) C 161) C 162) B 163) A 164) B 165) D 166) B 167) B 168) C 169) A 170) D 171) B 172) B 173) C 174) B 175) D 176) A 177) C 178) D 179) D 180) E 181) Section Break

181.1) C 181.2) D 181.3) B 181.4) D 181.5) E 181.6) B 182) E 183) D 184) C 185) B 186) D 187) B 188) B 189) D 190) C 191) B 192) A 193) C 194) E 195) D 196) D 197) A 198) D 199) C 200) A 201) D 202) B 203) A 204) B 205) E 206) C 207) A 208) A 209) A 210) B 211) A 212) C 213) A 214) D 215) B

216) 217) 218) 219) 220) 221) 222) 223) 224) 225) 226) 227) 228) 229) 230) 231) 232) 233) 234) 235) 236) 237) 238) 239) 240) 241) 242) 243) 244) 245) 246) 247) 248) 249) 250) 251) 252) 253) 254) 255)

C C B A D A D A C B A A A D D C D D C C B C A E A B C A B D E B A B B B A B B D

256) C 257) B 258) C 259) A 260) B 261) Section Break 261.1) A 261.2) B 261.3) D 261.4) B 261.5) A 262) A 263) C 264) B 265) D 266) A 267) D 268) C 269) A 270) D 271) C 272) A 273) D 274) C 275) A 276) B 277) D 278) A 279) C 280) D 281) A 282) A 283) B 284) A 285) D 286) C 287) A 288) B 289) C 290) A

291) D 292) A 293) B 294) C 295) B 296) C 297) A 298) Section Break 298.1) A 298.2) D 298.3) B 298.4) A 299) Section Break 299.1) C 299.2) A 299.3) A 299.4) C 299.5) B 299.6) A 299.7) B 299.8) C 299.9) D 299.10) C 299.11) C 300) Section Break 300.1) A 300.2) B 300.3) D 301) Section Break 301.1) A 301.2) D 301.3) B 302) D 303) B 304) A 305) A 306) B 307) C 308) B 309) D

310) Section Break 310.1) A 310.2) B 311) Section Break 311.1) B 311.2) C 311.3) D 311.4) C 311.5) D 311.6) D 311.7) D 311.8) A 312) Section Break 312.1) B 312.2) C 312.3) A 312.4) D 312.5) B 312.6) A 312.7) D 312.8) A 312.9) B 312.10) C 312.11) D 312.12) C 312.13) C 312.14) C 312.15) D

Student name:__________ 311)

i. A probability is usually expressed as a decimal, such as 0.70 or 0.27, but it may be given as a fraction, such as 7/10 or 27/100. ii. The closer a probability is to 0, the more likely that an event will happen. iii. The closer the probability is to 1.00, the more likely an event will not happen. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

312)

i. A probability is usually expressed as a decimal, such as 0.70 or 0.27, but it may be given as a fraction, such as 7/10 or 27/100. ii. The probability of 1 represents something that is certain to happen. iii. The probability of 0 represents something that cannot happen. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

313)

i. A probability is usually expressed as a decimal, such as 0.70 or 0.27, but it may be given as a fraction, such as 7/10 or 27/100. ii. The closer a probability is to 0, the more likely that an event will not happen. iii. The closer the probability is to 1.00, the more likely an event will happen. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

314)

i. The probability of an event, based on a classical approach, is defined as the number of favourable outcomes divided by the total number of possible outcomes. ii. If among several events only one can occur at a time, we refer to these events as being mutually exclusive events. iii. The probability of rolling a 3 or 2 on a single die is an example of conditional probability. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

315)

i. A subjective probability can be assigned to an event by an individual based on the individual's knowledge about the event. ii. The probability that you would assign to the likelihood that the Hamilton Tiger Cats will be in the Grey Cup this season must be between 0 and 1. iii. A probability is a number from -1 to +1 inclusive that measures one's belief that an event resulting from an experiment will occur. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

316)

i. The Cunard luxury liner, Queen Elizabeth 2, cannot be docked in Hong Kong and Bangkok at the same time. Events such as these that cannot occur simultaneously are said to be collectively exhaustive. ii. If there are 'm' ways of doing one thing and 'n' ways of doing another thing, the multiplication formula states that there are (m)(n) ways of doing both. iii. A permutation is an arrangement of a set of objects in which there is an order from the first through the last. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

317)

An electronics firm manufactures three models of stereo receivers, two cassette decks, four speakers and three CD players. When the four types of components are sold together, they form a "system." How many different systems can the electronic firm offer? A) 36 B) 18 C) 72 D) 144

318)

The numbers 0 through 9 are to be used in code groups of four to identify an item of clothing. Code 1083 might identify a blue blouse, size medium. The code group 2031 might identify a pair of pants, size 18, and so on. Repetitions of numbers are not permitted, i.e., the same number cannot be used more than once in a total sequence. As examples, 2256, 2562 or 5559 would not be permitted. How many different code groups can be designed? A) 5,040 B) 620 C) 10,200 D) 120

319)

There are two letters C and D. If repetitions such as CC are permitted, how many permutations are possible? A) 1 B) 0 C) 4 D) 8

320)

You have the assignment of designing colour codes for different parts. Three colours are to be used on each part, but a combination of three colours used for one part cannot be rearranged and used to identify a different part. This means that if green, yellow and violet were used to identify a camshaft, yellow, violet and green (or any other combination of these three colours) could not be used to identify a pinion gear. If there are 35 combinations, how many colours were available? A) 5 B) 7 C) 9 D) 11

321)

A builder has agreed not to erect all "lookalike" homes in a new subdivision. Five exterior designs are offered to potential homebuyers. The builder has standardized three interior plans that can be incorporated in any of the five exteriors. How many different ways are the exterior and interior plans offered to potential homebuyers? A) 8 B) 10 C) 15 D) 30

322)

Six basic colours are to be used in decorating a new condominium. They are to be applied to a unit in groups of four colours. One unit might have gold as the principal colour, blue as a complementary colour, red as the accent colour and touches of white. Another unit might have blue as the principal colour, white as the complimentary colour, gold as the accent colour and touches of red. If repetitions are permitted, how many different units can be decorated? A) 7,825 B) 24 C) 125 D) 1,296

323)

Six basic colours are to be used in decorating a new condominium. They are to be applied to a unit in groups of four colours. One unit might have gold as the principal colour, blue as a complementary colour, red as the accent colour and touches of white. Another unit might have blue as the principal colour, white as the complimentary colour, gold as the accent colour and touches of red. If repetitions are not permitted, how many different units can be decorated? A) 360 B) 25 C) 125 D) 1,296

324)

Consideration is being given to forming a Super Ten Basketball Conference. The top 10 university basketball teams in the country, based on past records, would be members of the Super Ten Conference. Each team would play every other team in the conference during the season and the team winning the most games would be declared the national champion. How many games would the conference commissioner have to schedule each year? (Remember, McMaster versus Alberta is the same as Alberta versus McMaster.) A) 45 B) 50 C) 125 D) 14

325)

A rug manufacturer has decided to use 7 compatible colours in her rugs. However, in weaving a rug, only 5 spindles can be used. In advertising, the rug manufacturer wants to indicate the number of different colour groupings for sale. How many colour groupings using the seven colours taken five at a time are there? (This assumes that 5 different colours will go into each rug, i.e., there are no repetitions of colour.) A) 120 B) 2,520 C) 6,740 D) 36

326)

i. An experiment is an activity that is either observed or measured. ii. If an experiment, such as a die-tossing experiment, has a set of events that includes every possible outcome, the set of events is called collectively exhaustive. iii. The combination formula is: n!/(n - r)! A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

327)

i. An illustration of an experiment is turning the ignition key of an automobile as it comes off the assembly line to determine whether or not the engine will start. ii. If there are 'm' ways of doing one thing and 'n' ways of doing another thing, the multiplication formula states that there are (m)*(n) ways of doing both. iii. A permutation is an arrangement of a set of objects in which there is an order from the first through the last. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

328)

A sales representative calls on four hospitals in York Region. It is immaterial what order he calls on them. How many ways can he organize his calls? A) 4 B) 24 C) 120 D) 37

329)

i. The Cunard luxury liner, Queen Elizabeth 2, cannot be docked in Hong Kong and Bangkok at the same time. Events such as these that cannot occur simultaneously are said to be mutually exclusive. ii. If there are 'm' ways of doing one thing and 'n' ways of doing another thing, the multiplication formula states that there are (m) • (n) ways of doing both. iii. A permutation is an arrangement of a set of objects in which order does not matter. A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

330)

What does A) 640 B) 36 C) 10 D) 120

331)

The result of a particular experiment is called a(n) A) observation. B) conditional probability. C) event. D) outcome.

equal?

332)

When are two events mutually exclusive? A) They overlap on a Venn diagram B) If one event occurs, then the other cannot C) Probability of one affects the probability of the other D) They both happen at the same time

333)

The National Centre for Health Statistics reported that of every 883 deaths in recent years, 24 resulted from an automobile accident, 182 from cancer and 333 from heart disease. Using the relative frequency approach, what is the probability that a particular death is due to an automobile accident? A) 24/883 or 0.027 B) 539/883 or 0.610 C) 24/333 or 0.072 D) 182/883 or 0.206

334)

Which approach to probability is exemplified by the following formula? Probability of Event Happening =

Number of times event occurred in past

Total number of observations A) Classical approach B) Empirical approach C) Subjective approach

335)

A study of 200 stamping firms revealed these incomes after taxes: Income After Taxes

Number of Firms

Under $1 million

102

$1 million to under $20 million

$20 million and more

What is the probability that a particular firm selected has $1 million or more in income after taxes? A) 0.00 B) 0.25 C) 0.49 D) 0.51

336)

According to which classification or type of probability are the events equally likely? A) Classical B) Empirical C) Subjective D) Mutually exclusive

337)

The first card selected from a standard 52-card deck was a king. If it is returned to the deck, what is the probability that a king will be drawn on the second selection? A) 1/4 or 0.25 B) 1/13 or 0.077 C) 12/13 or 0.923 D) 1/3 or 0.33

338)

A group of employees of Unique Services is to be surveyed with respect to a new pension plan. In-depth interviews are to be conducted with each employee selected in the sample. The employees are classified as follows. Classification

Event

Number of Employees

Supervisors

120

Maintenance

Production

1,460

Management

302

Secretarial

What is the probability that the first person selected is classified as a maintenance employee? A) 0.20 B) 0.50 C) 0.025 D) 1.00

339)

A lamp manufacturer has developed five lamp bases and four lampshades that could be used together. How many different arrangements of base and shade can be offered? A) 5 B) 10 C) 15 D) 20

340)

When two or more events can occur concurrently it is called A) conditional probability. B) empirical probability. C) joint probability. D) a tree diagram.

341)

When an event's probability depends on the likelihood of another event, the probability is A) conditional probability. B) empirical probability. C) joint probability. D) Mutually exclusive probability.

342)

A board of directors consists of eight men and four women. A four-member search committee is to be chosen at random to recommend a new company president. What is the probability that all four members of the search committee will be women? A) 1/120 or 0.00083 B) 1/16 or 0.0625 C) 1/8 or 0.125 D) 1/495 or 0.002

343)

When an experiment is conducted "without replacement", A) events are independent. B) events are equally likely. C) the experiment can be illustrated with a Venn Diagram. D) the probability of two or more events is computed as a joint probability.

344)

What does the complement rule state? A) P( A) = P( A) - P( B) B) P( A) = 1 - P (not A) C) P( A) = P( A) • P( B) D) P( A) = P( A) X + P( B)

345)

i. The complement rule states that the probability of an event not occurring is equal to one minus the probability of its occurrence. ii. If there are two independent events A and B, the probability that A and x B will occur is found by multiplying the two probabilities. Thus for two events A and B, the special rule of multiplication shown symbolically is: P( A and B) = P( A) P( B). iii. The general rule of multiplication is used to find the joint probability that two events will occur. Symbolically, the joint probability P( A and B) is found by: P( A and B) = P( A) P( B/A). A) (i), (ii) and (iii) are all correct statements B) (i) and, (ii) are correct statements but not (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

346)

Routine physical examinations are conducted annually as part of a health service program for the employees. It was discovered that 8% of the employees needed corrective shoes, 15% needed major dental work and 3% needed both corrective shoes and major dental work. What is the probability that an employee selected at random will need either corrective shoes or major dental work? A) 0.20 B) 0.25 C) 0.50 D) 1.00

347)

There are 10 rolls of film in a box and 3 are defective. Two rolls are to be selected one after the other. What is the probability of selecting a defective roll followed by another defective roll? A) 1/2 or 0.50 B) 1/4 or 0.25 C) 1/120, or about 0.0083 D) 1/15, or about 0.07

348)

Giorgio offers the person who purchases a 250 ml bottle of Allure two free gifts, either an umbrella, a 30 ml bottle of Midnight, a feminine shaving kit, a raincoat or a pair of rain boots. If you purchased Allure what is the probability you selected at random an umbrella and a shaving kit in that order? A) 0.00 B) 1.00 C) 0.05 D) 0.20

349)

The machine has just been filled with 50 black, 150 white, 100 red and 100 yellow gum balls that have been thoroughly mixed. Sue and Jim approached the machine first. They both said they wanted red gum balls. What is the likelihood they will get their wish? A) 0.50 B) 0.062 C) 0.33 D) 0.75

350)

A survey of top executives revealed that 35% of them regularly read Time magazine, 20% read Newsweek and 40% read Macleans & World Report. Ten percent read both Time and Macleans. What is the probability that a particular top executive reads either Time or Macleans regularly? A) 0.85 B) 0.06 C) 1.00 D) 0.65

351)

A study by Tourism Ontario revealed that 50% of the vacationers going to Toronto visit the CN Tower, 40% visit SkyDome and 35% visit both. What is the probability that a vacationer will visit at least one of these magnificent attractions? A) 0.95 B) 0.35 C) 0.55 D) 0.05

i. A coin is tossed four times. The probability is ¼ or 0.25 that all four tosses will result in a head face up. ii. A coin is tossed four times. The probability is 1/16 or 0.0625 that all four tosses will result in a head face up. iii. If two events are mutually exclusive, then P( A or B) = P( A) P( B). A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (ii) is a correct statement but not(i) and (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

352)

353)

A tire manufacturer advertises, "the median life of our new all-season radial tire is 120,000 km. An immediate adjustment will be made on any tire that does not last 120,000 km." You purchased four of these tires. What is the probability that all four tires will wear out before traveling 120,000 km? A) 1/10 or 0.10 B) ¼ or 0.25 C) 1/64 or 0.0156 D) 1/16 or 0.0625

354)

Three defective electric toothbrushes were accidentally shipped to a drugstore by the manufacturer along with 17 non-defective ones. What is the probability that the first two electric toothbrushes sold will be returned to the drugstore because they are defective? A) 3/20 or 0.15 B) 3/17 or 0.176 C) 1/4 or 0.25 D) 3/190 or 0.01579

355)

If two events are independent, then their joint probability is A) computed with the special rule of addition B) computed with the special rule of multiplication C) computed with the general rule of multiplication D) computed with Bayes theorem

356)

When applying the special rule of addition for mutually exclusive events, the joint probability is: A) 1 B) 5 C) 0 D) 0.25 E) unknown

357)

Event

Number of Employees

Supervisors

120

Maintenance

Production

1,460

Management

302

Secretarial

357.1) What is the probability that the first person selected is either in maintenance or in

secretarial? A) 0.200 B) 0.015 C) 0.085 D) 0.001

357.2) What is the probability that the first person selected is in management and in supervision? A) 0.00 B) 0.06 C) 0.15 D) 0.21

357.3) What is the probability that the first person selected is a supervisor and in production? A) 0.00 B) 0.06 C) 0.15 D) 0.21

358)

Each salesperson in a large department store chain is rated with respect to sales potential for advancement. These traits for the 500 salespeople were cross classified into the following table. Sales Ability

Fair

Good

Excellent

Below average

Average

Above average

135

358.1) What is the probability that a salesperson selected at random has above average sales

ability and is an excellent potential for advancement? A) 0.20 B) 0.50 C) 0.27 D) 0.75

358.2) What is the probability that a salesperson selected at random will have average sales

ability and good potential for advancement? A) 0.09 B) 0.12 C) 0.30 D) 0.525

358.3) What is the probability that a salesperson selected at random will have below average

sales ability and fair potential for advancement? A) 0.032 B) 0.10 C) 0.16 D) 0.32

359)

A study of the opinion of designers with respect to the primary colour most desirable for use in executive offices showed that: Primary Colour

Number of Opinions

Red

Orange

Yellow

Green

Blue

Indigo

Violet

359.1) What is the probability that a designer does not prefer red? A) 1.00 B) 0.77 C) 0.73 D) 0.23

359.2) What is the probability that a designer does not prefer yellow? A) 0.000 B) 0.765 C) 0.885 D) 1.000

359.3) What is the probability that a designer does not prefer blue? A) 1.0000 B) 0.9075 C) 0.8850 D) 0.7725

360)

An automatic machine inserts mixed vegetables into a plastic bag. Past experience revealed that some packages were underweight and some were overweight, but most of them had satisfactory weight. Weight

% of Total

Underweight

2.5

Satisfactory

90.0

Overweight

7.5

360.1) What is the probability of selecting and finding that all three of them are overweight? A) 0.0000156 B) 0.0004218 C) 0.0000001 D) 0.075

360.2) What is the probability of selecting and finding that all three of them are satisfactory? A) 0.900 B) 0.810 C) 0.729 D) 0.075

361)

The following distribution table represents preferences for two types of cereals by 2000 boys and girls. Prefers Fruity cereal

Prefers nutty cereal

Total

Boys

500

1,000

Girls

700

300

1,000

361.1) Find the probability that an individual selected at random will be a boy and prefer Fruity

cereal. A) B) C) D)

500/1,000 500/2,000 1,200/2,000 500/1,200

361.2) What is the probability that an individual, whether a boy or girl, prefers nutty cereal? A) 500/1,000 B) 500/2,000 C) 1,200/2,000 D) 500/1,200 E) 800/2000

361.3) Find the probability that a person prefers Fruity cereal given that the person is a boy. A) 500/1,000 B) 500/2,000 C) 1,200/2,000 D) 500/1,200

361.4) Determine the probability that the person is a boy, given that the person likes Fruity

Cereal. A) B) C) D)

500/1,000 500/2,000 1,200/2,000 500/1,200

362)

The customer service department of H&R Block received a total of 235 telephone requests for a tip-sheet on personal tax or corporate tax. The following table summarizes callers' primary area of interest, and how they first heard about the tip-sheet. Topic of most interest to caller

How the caller first heard about the report Radio

Newspaper

Television

Internet

Personal tax

Corporate tax

If one person is randomly selected, what is the likelihood that the caller first heard about the report from Television, given that the topic of interest is personal tax? A) 40/235 B) 26/100 C) 20/100 D) 20/235

363)

Type of Attack Relationship of Criminal to Victim

Type of Attack Homicide

Robbery

Assault

Totals

Stranger

389

757

1166

Acquaintance or Relative

116

669

834

Totals

505

1426

2000

363.1) If one person is randomly selected, what is the likelihood that he or she was victimized

by a stranger, given that a robbery victim is selected? A) 389/505 B) 389/1,118 C) 389/2,000 D) 1,234/2,000

363.2) Given that an assault victim is selected, what is the likelihood that the criminal is a

stranger? A) 757/2000 B) 1787/2000 C) 757/1426 D) 1426/2000

363.3) What is the likelihood of a victim being attacked by a relative or acquaintance? A) 389/505 B) 834/2000 C) 389/2000 D) 1166/2000

363.4) Find the probability that when 1 of the 2000 subjects is randomly selected, the person

chosen was robbed or was victimized by an acquaintance or relative. A) 1223/2000 B) 903/1000 C) 1292/2000 D) 1234/2000

363.5) If two different subjects are randomly selected, find the probability that they were both

robbed. A) 27.5% B) 25.5% C) 55% D) 6.4%

363.6) If one person is randomly selected, find the probability that they were victimized by a

stranger. A) 389/1166 B) 389/834 C) 1166/2000 D) 1234/2000

364)

A survey of 500 top Canadian companies reported what the companies' hiring outlook was for the next 18 months as well as the general company outlook for the economy over the same period of time. Economy Outlook

Add Jobs

Hiring Outlook No Change

Cut Jobs

Favourable

100

Unknown

150

Unfavourable

364.1) What is the probability that a randomly selected company from this sample does not have

a favourable outlook for the economy over the next 18 months? A) 325/500 B) 260/500 C) 175/500 D) 65/500

364.2) Given that a randomly selected company plans to add jobs during the next 18 months,

what is the probability that they have a favourable outlook for the economy? A) 325/500 B) 165/500 C) 175/500 D) 235/500 E) 100/165

364.3) Given that a randomly selected company plans to add jobs during the next 18 months,

what is the probability that they have an unfavourable outlook for the economy? A) 325/500 B) 100/175 C) 175/500 D) 100/165 E) 15/165

364.4) What is the probability that a randomly selected company plans to cut jobs during the

next 18 months? A) 125/500 B) 375/500 C) 210/500 D) 25/500

364.5) What is the probability that a randomly selected company does not plan to add jobs

during the next 18 months? A) 165/500 B) 335/500 C) 210/500 D) 25/500

364.6) Given that a randomly selected company has a favourable forecast, what is the

probability that it plans to cut jobs during the next 18 months? A) 25/500 B) 25/175 C) 125/175 D) 175/500

364.7) What is the probability that a randomly selected company has an unfavourable forecast

for the economy for the next 18 months? A) 25/500 B) 325/500 C) 65/500 D) 175/500

365)

An insurance company has collected the following data on the gender and marital status of 400 customers. Gender

Single

Married

Divorced

Male

125

Female

365.1) Suppose that a customer is selected at random. Find the probability that the customer

selected is not single. A) 75/400 B) 175/400 C) 150/400 D) 325/400

365.2) Suppose that a customer is selected at random. Find the probability that the customer

selected is married if the customer is male. A) 125/240 B) 175/400 C) 125/175 D) 175/240

365.3) Suppose that a customer is selected at random. Find the probability that the customer

selected is married if the customer is female. A) 125/240 B) 50/160 C) 110/160 D) 50/400

365.4) Suppose that a customer is selected at random. Is it more likely to be a single female or a

single male? Determine the probabilities of each. A) P(single male) = 25/240, P(single female) = 50/160, therefore more likely to be a single male B) P(single male) = 25/400, P(single female) = 50/400, therefore more likely to be a single female. C) P(single male) = 290/400, P(single female) = 185/400, therefore more likely to be a single male D) P(single male) = P(single female) therefore equally likely

366)

Each salesperson in a large department store chain is rated with respect to sales potential for advancement. These traits for the 500 salespeople were cross-classified into the following table: Potential for Advancement Sales Ability

Fair

Good

Excellent

Below average

Average

Above average

135

366.1) What is the probability that the selected salesperson has below average sales ability? A) 50/500 B) 150/500 C) 300/500 D) 16/50 E) 154/500

366.2) 81 What is the probability that the selected salesperson has above average sales ability? A) 50/500 B) 150/500 C) 300/500 D) 16/50 E) 154/500

366.3) What is the probability that the selected salesperson has average sales ability? A) 50/500 B) 150/500 C) 300/500 D) 16/50 E) 154/500

366.4) What is the probability that the selected salesperson has below average sales ability or

has a fair potential for advancement? A) 16/500 B) 16/154 C) 300/500 D) 188/500 E) 204/500

366.5) What is the probability that the selected salesperson has below average sales ability and

has a fair potential for advancement? A) 16/500 B) 16/154 C) 300/500 D) 188/500 E) 204/500

366.6) What is the probability that the selected salesperson has a fair potential for advancement,

given that they have a below average ability? A) 16/500 B) 16/154 C) 16/50 D) 188/500 E) 204/500

367)

How the caller first heard about the report Radio

Newspaper

Television

Internet

Personal tax

Corporate tax

367.1) What is the probability a caller became aware of the tip-sheet either by radio or

newspaper given her primary interest is corporate tax? A) 106/135 B) 36/135 C) 70/135 D) 90/235 E) 160/235

367.2) What is the probability a caller is interested in personal tax given that he first heard of the

tip-sheet in the newspaper? A) 106/135 B) 20/90 C) 70/135 D) 90/235 E) 70/90

368)

A tire manufacturer truthfully advertises that "the average life of our new all-season radial tire is 100,000 kilometres." You purchase four of these tires. What is the probability that all four tires will wear out before traveling 100,000 kilometres? A) 1/10 or 0.10 B) ¼ or 0.25 C) 1/16 or 0.0625. D) 1/8 or 0.125 E) ½ or 0.50

369)

Information on the 30 Major League Baseball teams for the 2019 season has been summarized based on game attendance. Attendance <2 mil

2 mil to <3 mil

3 mil to <4 mil

Win

Lose

Total

369.1) What is the probability that if a team is selected at random, it had a winning season? A) 18/30 B) 6/11 C) 6/30 D) 12/30

369.2) What is the probability that if a team is selected at random, it had a winning season or

attendance of more than 3.0 million? A) 18/30 B) 19/30 C) 13/30 D) 9/30 E) 12/30

369.3) What is the probability that if a team is selected at random had attendance of more than

3.0 million, that it had a winning season? A) 4/18 B) 4/30 C) 18/30 D) 4/5 E) 12/30

369.4) What is the probability that if a team is selected at random, it had a losing season and

drew attendance of less than 2.0 million? A) 18/30 B) 5/30 C) 13/30 D) 9/30 E) 12/30

370)

You take a trip by air that involves three independent flights. If there is a 90 percent chance each specific leg of the trip is done on time, what is the probability all three flights arrive on time? A) 0.729 B) 0.810 C) 0.270 D) 0.271 E) 0.000

371)

You take a trip by air that involves three independent flights. If there is a 90 percent chance each specific leg of the trip is done on time, what is the probability all three flights are late? A) 0.729 B) 0.810 C) 0.270 D) 0.271 E) 0.001

372)

Crime Statistics Type of Crime

Under 20 years

20 to 40 years

Over 40 years

Total

Violent

Nonviolent

Total

150

372.1) What is the probability that if you select one person at random that they have committed

a violent crime? A) 54.7% B) 45.3% C) 36.7% D) 53.3%

372.2) What is the probability that if you select one person at random that they have committed

a nonviolent crime? A) 54.7% B) 45.3% C) 36.7% D) 53.3%

372.3) What is the probability that if you select one person at random that they have committed

a violent crime and were under 20 years of age? A) 8% B) 18% C) 26% D) 62.7%

372.4) What is the probability that if you select one person at random that they have committed

a violent crime and were at least 20 years of age? A) 36.7% B) 18% C) 26% D) 27.3%

372.5) What is the probability that if you select one person at random that they have committed

a violent crime and were over 40 years of age? A) 36.7% B) 5.6% C) 18.1% D) 9.3%

372.6) What is the probability that if you select one person at random that they have committed

a violent crime and were under 20 or over 40 years of age? A) 18.01% B) 56.23% C) 50.00% D) 9.3%

372.7) What is the probability that if you select one person at random that they committed a

violent crime, given that they were under 20 years of age? A) 74.00% B) 69.2% C) 30.8% D) 9.3%

372.8) What is the probability that if you select one person at random that they have committed

a violent crime, given that they were between 20 and 40 years of age? A) 54.67% B) 56.23% C) 50.00% D) 18.0%

372.9) What is the probability that if you select one person at random that they committed a

nonviolent crime, given that they were under 20 years of age? A) 74.00% B) 69.2% C) 30.8% D) 9.3%

372.10) What is the probability that if you select one person at random that they committed a

violent crime, given that they were over 40 years of age? A) 74.00% B) 38.9% C) 30.8% D) 61.1%

373)

A visual means useful in calculating joint and conditional probability is A) a tree diagram. B) a Venn diagram. C) a histogram. D) an inferential statistic.

374)

In a management trainee program, 80 percent of the trainees are female, 20 percent male. Ninety percent of the females attended college, 78 percent of the males attended college. A management trainee is selected at random. What is the probability that the person selected is a female who did NOT attend college? A) 0.20 B) 0.08 C) 0.25 D) 0.80

375)

(i) If there is absolutely no chance a person will purchase a new car this year, the probability assigned to this event is zero. (ii) If the set of events are collectively exhaustive and mutually exclusive, the sum of the probabilities equals 1. (iii) Suppose four heads did appear face up on the toss of a coin four times. The probability that a head will appear face up in the next toss of the coin is 1/2 or 0.5. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

376)

(i) If there is absolutely no chance a person will purchase a new car this year, the probability assigned to this event is zero. (ii) If the set of events are collectively exhaustive and mutually exclusive, the sum of the probabilities equals 0. (iii) Suppose four heads did appear face up on the toss of a coin four times. The probability that a head will appear face up in the next toss of the coin is 1/2 or 0.5. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

377)

(i) If there is absolutely no chance a person will purchase a new car this year, the probability assigned to this event is 0.5. (ii) If the set of events are collectively exhaustive and mutually exclusive, the sum of the probabilities equals 1. (iii) Suppose four heads did appear face up on the toss of a coin four times. The probability that a head will appear face up in the next toss of the coin is 1/2 or 0.5. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

378)

(i) When the special rule of multiplication is used events A and B must be independent. (ii) A probability is subjective if it is based on a person's degree of belief and hunches that a particular event will happen. (iii) If there are five vacant parking places and five automobiles arrive at the same time, they can park in 120 different ways. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

379)

(i) When the special rule of multiplication is used events A and B must be conditional. (ii) A probability is subjective if it is based on a person's degree of belief and hunches that a particular event will happen. (iii) If there are five vacant parking places and five automobiles arrive at the same time, they can park in 120 different ways. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

380)

(i) When the special rule of multiplication is used events A and B must be independent. (ii) A probability is subjective if it is based on a person's degree of belief and hunches that a particular event will happen. (iii) If there are five vacant parking places and five automobiles arrive at the same time, they can park in 25 different ways. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) and, (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

381)

(i) A new computer game has been developed and its market potential is to be tested by 80 veteran game players. If sixty players liked the game, the probability that veteran game players will like the new computer game is 3/4 or 0.75. (ii) A probability that is based on someone's opinion, guess or hunch is subjective. (iii) The probability that a one-spot or a two-spot or a six-spot will appear face up on the throw of one die is 1/2 or 0.5. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) and, (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

382)

(i) A company has warehouses in four regions: South, Midwest, Rocky Mountain and Far West. One warehouse is to be selected at random to store a seldom-used item. The probability that the warehouse selected would be the one in the Far West region is 1/4 or 0.25. (ii) One card from a standard 52-card deck of cards is to be selected at random. The probability that it will be the jack of hearts is 1/52 or 0.0192. (iii) An activity that is measured or observed is called a(n) experiment. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

383)

(i) A company has warehouses in four regions: South, Midwest, Rocky Mountain and Far West. One warehouse is to be selected at random to store a seldom-used item. The probability that the warehouse selected would be the one in the Far West region is 0.20. (ii) One card from a standard 52-card deck of cards is to be selected at random. The probability that it will be the jack of hearts is 1/52 or 0.0192. (iii) An activity that is measured or observed is called a(n) experiment. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

384)

(i) A new computer game has been developed and its market potential is to be tested by 80 veteran game players. If sixty players liked the game, the probability that veteran game players will like the new computer game is 0.60. (ii) A probability that is based on someone's opinion, guess or hunch is subjective. (iii) The probability that a one-spot or a two-spot or a six-spot will appear face up on the throw of one die is 1/2 or 0.5. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

385)

(i) A new computer game has been developed and its market potential is to be tested by 80 veteran game players. If sixty players liked the game, the probability that veteran game players will like the new computer game is 3/4 or 0.75. (ii) A probability that is based on someone's opinion, guess or hunch is joint. (iii) The probability that a one-spot or a two-spot or a six-spot will appear face up on the throw of one die is 1/2 or 0.5. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) and, (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

386)

(i) A particular result of an experiment is called a(n) outcome. (ii) When the occurrence of one event does not affect the occurrence of the other event, the two events are dependent. (iii) If the order of a set of objects is important, it is called permutation. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) and, (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

387)

(i) A particular result of an experiment is called a(n) outcome. (ii) When the occurrence of one event does not affect the occurrence of the other event, the two events are independent. (iii) If the order of a set of objects is important, it is called permutation. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) and, (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

388)

(i) A particular result of an experiment is called a(n) outcome. (ii) When the occurrence of one event does not affect the occurrence of the other event, the two events are independent. (iii) If the order of a set of objects is important, it is called combination. A) (i), (ii) and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (i) and, (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

389)

A study was done of the 377 vehicles parked in the college parking lot last Friday. The results are as follows. Red

Black

Blue

Grey

White

Total

SUV ’s

133

Sports

121

Compact

123

Total

105

377

389.1) What is the probability of finding a red car? A) 20/377 B) 47/377 C) 47/133 D) 20/133

389.2) What is the probability of finding a car that is not white? A) 60/377 B) 317/377 C) 47/60 D) 361/377

389.3) What is the probability of finding a sports car or a compact car? A) 121/377 B) 123/377 C) 244/377 D) 133/377

389.4) What is the probability of finding a red sports car? A) 15/47 B) 15/121 C) 15/377 D) 153/377

389.5) What is the probability of finding a sports car, given that you are looking for a red car? A) 15/47 B) 15/121 C) 15/377 D) 153/377

389.6) What is the probability of finding a vehicle that is both an SUV and either blue or grey in

colour? A) B) C) D)

36/133 15/121 61/133 61/377

389.7) What is the probability of finding a vehicle that is either a SUV or grey in colour? A) 36/133 B) 36/93 C) 190/377 D) 61/377

390)

How the caller first heard about the report Radio

Newspaper

Television

Internet

Personal tax

Corporate tax

390.1) Suppose that a caller is selected at random. Find the probability that the caller selected

heard about the report from the radio, assuming they are interested in personal tax. A) 34/100 B) 34/235 C) 34/135 D) 34/70A

390.2) Suppose that a caller is selected at random. Find the probability that the caller selected is

interested in personal tax, if they heard about the report from the radio. A) 34/100 B) 34/235 C) 34/135 D) 34/70

390.3) Suppose that a caller is selected at random. Are they more likely to be interested in

personal tax and first heard about the report from the radio, or more likely to be interested in corporate tax and first heard about the report from the radio? A) P(personal and radio) = 34/100, P(corporate and radio) = 36/100, therefore they are more likely to be interested in corporate tax and first heard about the report from the radio. B) P(personal and radio) = 34/235, P(corporate and radio) = 36/235, therefore they are more likely to be interested in corporate tax and first heard about the report from the radio. C) P(personal and radio) = 34/135, P(corporate and radio) = 36/135, therefore they are more likely to be interested in corporate tax and first heard about the report from the radio. D) Insufficient information to determine the answer.

391)

Refer to the following table of patient's admission age versus the number of vaccinations taken during the fourth wave of the pandemic: # of Vaccinations Age

Total

12-17

160

199

18-39

180

248

40-65

Over 65

Total

420

140

570

391.1) What is the probability the next patient admitted is in the class with an age of 12-17? A) 0.06 B) 0.15 C) 0.35 D) 0.44

391.2) What is the probability the next patient admitted is in the class with an age of 18-39? A) 0.06 B) 0.15 C) 0.35 D) 0.44

391.3) What is the probability the next patient admitted is in the class with an age of 40-65? A) 0.06 B) 0.15 C) 0.35 D) 0.44

391.4) What is the probability the next patient admitted is in the class with an age of over 65? A) 0.06 B) 0.15 C) 0.35 D) 0.44

391.5) What is the probability the next patient admitted was not vaccinated? A) 0.02 B) 0.10 C) 0.25 D) 0.74

391.6) What is the probability the next patient admitted had exactly 1 vaccination? A) 0.02 B) 0.10 C) 0.25 D) 0.74

391.7) What is the probability the next patient admitted had exactly 2 vaccinations? A) 0.02 B) 0.10 C) 0.25 D) 0.74

391.8) What is the probability the next patient admitted had at least 1 vaccination? A) 0.02 B) 0.10 C) 0.26 D) 0.98

391.9) What is the probability the next patient admitted had no more than 1 vaccination? A) 0.02 B) 0.10 C) 0.26 D) 0.98

391.10) What is the probability the next patient admitted is less than 40? A) 0.10 B) 0.20 C) 0.78 D) 1.0

391.11) What is the probability the next patient admitted is 40 or more? A) 0.10 B) 0.22 C) 0.80 D) 1.0

391.12) What is the probability the next patient admitted is 12-17 and is not vaccinated? A) 0.01 B) 0.06 C) 0.11 D) 0.28

391.13) What is the probability the next patient admitted is 12-17 and has 1 vaccination? A) 0.01 B) 0.06 C) 0.11 D) 0.28

391.14) What is the probability the next patient admitted is 12-17 and has 2 vaccinations? A) 0.01 B) 0.06 C) 0.11 D) 0.28

391.15) What is the probability the next patient admitted is 18-39 and has 0 vaccination? A) 0.01 B) 0.11 C) 0.28 D) 0.32

391.16) What is the probability the next patient admitted is 18-39 and has 1 vaccination? A) 0.01 B) 0.11 C) 0.28 D) 0.32

391.17) What is the probability the next patient admitted is 18-39 and has 2 vaccinations? A) 0.01 B) 0.11 C) 0.28 D) 0.32

391.18) What is the probability the next patient admitted is 40-65 and has 0 vaccinations? A) 0.00 B) 0.04 C) 0.11 D) 0.28

391.19) What is the probability the next patient admitted is 40-65 and has 1 vaccination? A) 0.00 B) 0.04 C) 0.11 D) 0.28

391.20) What is the probability the next patient admitted is 40-65 and has 2 vaccinations? A) 0.00 B) 0.04 C) 0.11 D) 0.28

391.21) What is the probability the next patient admitted is over 65 and has 0 vaccinations? A) 0.00 B) 0.01 C) 0.03 D) 0.04

391.22) What is the probability the next patient admitted is over 65 and has 1 vaccination? A) 0.00 B) 0.01 C) 0.03 D) 0.04

391.23) What is the probability the next patient admitted is over 65 and has 2 vaccinations? A) 0.00 B) 0.01 C) 0.03 D) 0.04

391.24) What is the probability the next patient admitted is 12-17 or has 0 vaccinations? A) 0.36 B) 0.53 C) 0.61 D) 0.81

391.25) What is the probability the next patient admitted is 12-17 or has 1 vaccination? A) 0.36 B) 0.53 C) 0.61 D) 0.81

391.26) What is the probability the next patient admitted is 12-17 or has 2 vaccinations? A) 0.36 B) 0.53 C) 0.61 D) 0.81

391.27) What is the probability the next patient admitted is 18-39 or has 0 vaccinations? A) 0.45 B) 0.57 C) 0.86 D) 0.95

391.28) What is the probability the next patient admitted is 18-39 or has 1 vaccination? A) 0.45 B) 0.57 C) 0.86 D) 0.95

391.29) What is the probability the next patient admitted is 18-39 or has 2 vaccinations? A) 0.45 B) 0.57 C) 0.86 D) 0.95

391.30) What is the probability the next patient admitted is 40-65 or has 0 vaccinations? A) 0.17 B) 0.35 C) 0.53 D) 0.78

391.31) What is the probability the next patient admitted is 40-65 or has 1 vaccination? A) 0.17 B) 0.35 C) 0.53 D) 0.78

391.32) What is the probability the next patient admitted is 40-65 or has 2 vaccinations? A) 0.17 B) 0.35 C) 0.53 D) 0.78

391.33) What is the probability the next patient admitted is over 65 or has 0 vaccinations? A) 0.08 B) 0.28 C) 0.56 D) 0.76

391.34) What is the probability the next patient admitted is over 65 or has 1 vaccination? A) 0.08 B) 0.28 C) 0.56 D) 0.76

391.35) What is the probability the next patient admitted is over 65 or has 2 vaccinations? A) 0.08 B) 0.28 C) 0.56 D) 0.76

391.36) What is the probability the next patient admitted is 12-17 given that they have 0

vaccinations? A) 0.25 B) 0.35 C) 0.38 D) 0.40

391.37) What is the probability the next patient admitted is 12-17 given that they have 1

vaccination? A) 0.25 B) 0.35 C) 0.38 D) 0.40

391.38) What is the probability the next patient admitted is 12-17 given that they have 2

vaccinations? A) 0.25 B) 0.35 C) 0.38 D) 0.40

391.39) What is the probability the next patient admitted is 18-39 given that they have 0

vaccinations? A) 0.30 B) 0.40 C) 0.43 D) 0.46

391.40) What is the probability the next patient admitted is 18-39 given that they have 1

vaccination? A) 0.30 B) 0.40 C) 0.43 D) 0.46

391.41) What is the probability the next patient admitted is 18-39 given that they have 2

vaccinations? A) 0.30 B) 0.40 C) 0.43 D) 0.46

391.42) What is the probability the next patient admitted is 40-65 given that they have 0

vaccinations? A) 0.14 B) 0.16 C) 0.18 D) 0.20

391.43) What is the probability the next patient admitted is 40-65 given that they have 1

vaccination? A) 0.14 B) 0.16 C) 0.18 D) 0.20

391.44) What is the probability the next patient admitted is 40-65 given that they have 2

vaccinations? A) 0.14 B) 0.16 C) 0.18 D) 0.20

391.45) What is the probability the next patient admitted is over 65 given that they have 0

vaccinations? A) 0.02 B) 0.05 C) 0.10 D) 0.11

391.46) What is the probability the next patient admitted is over 65 given that they have 1

vaccination? A) 0.02 B) 0.05 C) 0.10 D) 0.11

391.47) What is the probability the next patient admitted is over 65 given that they have 2

vaccinations? A) 0.02 B) 0.05 C) 0.10 D) 0.11

391.48) What is the probability the next patient admitted has 0 vaccinations given they're 12-17? A) 0.01 B) 0.02 C) 0.18 D) 0.80

391.49) What is the probability the next patient admitted has 1 vaccination given they're 12-17? A) 0.01 B) 0.02 C) 0.18 D) 0.80

391.50) What is the probability the next patient admitted has 2 vaccinations given they're 12-17? A) 0.01 B) 0.02 C) 0.18 D) 0.80

391.51) What is the probability the next patient admitted has 0 vaccinations given they're 18-39? A) 0.01 B) 0.26 C) 0.73 D) 0.93

391.52) What is the probability the next patient admitted has 1 vaccination given they're 18-39? A) 0.01 B) 0.26 C) 0.73 D) 0.93

391.53) What is the probability the next patient admitted has 2 vaccinations given they're 18-39? A) 0.01 B) 0.26 C) 0.73 D) 0.93

391.54) What is the probability the next patient admitted has 0 vaccinations given they're 40-65? A) 0.01 B) 0.02 C) 0.29 D) 0.69

391.55) What is the probability the next patient admitted has 1 vaccination given they're 40-65? A) 0.01 B) 0.02 C) 0.29 D) 0.69

391.56) What is the probability the next patient admitted has 2 vaccinations given they're 40-65? A) 0.01 B) 0.02 C) 0.29 D) 0.69

391.57) What is the probability the next patient admitted has 0 vaccinations given they're over

65? A) B) C) D)

0.03 0.13 0.42 0.56

391.58) What is the probability the next patient admitted has 1 vaccination given they're over 65? A) 0.03 B) 0.13 C) 0.42 D) 0.56

391.59) What is the probability the next patient admitted has 2 vaccinations given they're over

65? A) B) C) D)

0.03 0.13 0.42 0.56

Answer Key Test name: chapter 4 313) 314) 315) 316) 317) 318) 319) 320) 321) 322) 323) 324) 325) 326) 327) 328) 329) 330) 331) 332) 333) 334) 335) 336) 337) 338) 339) 340) 341) 342) 343) 344) 345) 346) 347) 348) 349)

B A A B B D C A C B C D A A B B A B B C D B A B C A B C D C A D D B A A D

350) C 351) B 352) D 353) C 354) C 355) D 356) D 357) B 358) C 359) Section Break 359.1) C 359.2) A 359.3) A 360) Section Break 360.1) C 360.2) B 360.3) A 361) Section Break 361.1) B 361.2) C 361.3) B 362) Section Break 362.1) B 362.2) C 363) Section Break 363.1) B 363.2) E 363.3) A 363.4) D 364) B 365) Section Break 365.1) A 365.2) C 365.3) B 365.4) A 365.5) D 365.6) C 366) Section Break 366.1) A 366.2) E

366.3) E 366.4) A 366.5) B 366.6) B 366.7) C 367) Section Break 367.1) D 367.2) A 367.3) B 367.4) B 368) Section Break 368.1) A 368.2) C 368.3) B 368.4) D 368.5) A 368.6) C 369) Section Break 369.1) A 369.2) B 370) C 371) Section Break 371.1) A 371.2) B 371.3) D 371.4) B 372) A 373) E 374) Section Break 374.1) A 374.2) B 374.3) B 374.4) A 374.5) D 374.6) C 374.7) B 374.8) A 374.9) C 374.10) B 375) A

376) B 377) A 378) C 379) D 380) A 381) D 382) D 383) A 384) A 385) D 386) D 387) C 388) C 389) A 390) D 391) Section Break 391.1) B 391.2) B 391.3) C 391.4) C 391.5) A 391.6) D 391.7) C 392) Section Break 392.1) A 392.2) D 392.3) B 393) Section Break 393.1) C 393.2) D 393.3) B 393.4) A 393.5) D 393.6) C 393.7) A 393.8) C 393.9) D 393.10) C 393.11) B 393.12) D

393.13) B 393.14) A 393.15) D 393.16) B 393.17) A 393.18) C 393.19) B 393.20) A 393.21) D 393.22) C 393.23) A 393.24) D 393.25) B 393.26) A 393.27) C 393.28) B 393.29) A 393.30) D 393.31) B 393.32) A 393.33) D 393.34) B 393.35) A 393.36) C 393.37) A 393.38) D 393.39) C 393.40) D 393.41) A 393.42) A 393.43) C 393.44) D 393.45) B 393.46) D 393.47) C 393.48) D 393.49) C 393.50) B 393.51) C 393.52) B

393.53) A 393.54) D 393.55) C 393.56) B 393.57) D 393.58) C 393.59) A

Student name:__________ 392)

i. A random variable is assigned numerical values based on the outcomes of an experiment. ii. A random variable is a quantity resulting from a random experiment that can assume different values by chance. iii. The mean of a probability distribution is referred to as its expected value. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

393)

i. The probability of a particular outcome, designated X, must always be between 0 and 100 inclusive. ii. A random variable is a quantity resulting from a random experiment that can assume different values by chance. iii. The mean of a probability distribution is referred to as its expected value. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

394)

i. The probability of a particular outcome, designated X, must always be between 0 and 1 inclusive. ii. A random variable represents the outcomes of an experiment. iii. The mean of a probability distribution is referred to as its expected value. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

395)

i. A probability distribution is a mutually exclusive listing of experimental outcomes that can occur by chance and their corresponding probabilities. ii. The probability of a particular outcome, designated X, must always be between 0 and 10 inclusive. iii. The standard deviation of a probability distribution is referred to as its expected value. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

396)

What is a listing of all possible outcomes of an experiment and their corresponding probability of occurrence called? A) Random variable B) Probability distribution C) Subjective probability D) Frequency distribution

397)

What is the following table called? Number of Heads

A) B) C) D)

398)

Probability of Outcome

1/8 = 0.125

3/8 = 0.375

1/8 = 0.125

Total

8/8 = 1.000

Probability distribution Ogive Standard deviation Frequency table

Which of the following is correct about a probability distribution?

(i) Sum of all possible outcomes must equal 1. (ii) Outcomes must be mutually exclusive. (iii) Probability of each outcome must be between 0 and 100 inclusive. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

399)

Which of the following is correct about a probability distribution?

(i) Sum of all possible outcomes must equal 1. (ii) Outcomes must be mutually exclusive. (iii) Probability of each outcome must be between 0 and 1 inclusive. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

400)

A company is studying the number of monthly absences among its 125 employees. The following probability distribution shows the likelihood that people were absent 0, 1, 2, 3, 4 or 5 days last month. Number of days absent

Probability

0.60

0.20

0.12

0.04

400.1) Given the probability distribution, which of the following predictions is correct? A) 60% of the employees will have more than one day absent for a month. B) There is a 0.04 probability that an employee will be absent 1 day during a month. C) There is a 0.12 probability that an employee will be absent 2 days during a month. D) There is a 0.50 probability that an employee will be absent 0.72 days during a month.

400.2) What is the mean number of days absent? A) 1.00 B) 0.40 C) 0.72 D) 2.5

400.3) What is the variance of the number of days absent? A) 1.16 B) 1.41 C) 5.00 D) 55.52

401)

i. If we measure the weight of an eggnog carton, the variable is referred to as being a discrete random variable. ii. If we toss two coins and count the number of heads, there could be 0, 1, or 2 heads. Since the exact number of heads resulting from this experiment is due to chance, the number of heads appearing is a random variable. iii. A random variable may be either discrete or continuous. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

402)

i. A random variable may be either discrete or continuous. ii. If Unique Buying Services has 100 employees, there might be 0, 1, 2, 3 up to 100 employees absent on Monday. In this case, the day of the week is the random variable. iii. If we measure the weight of an eggnog carton, the variable is referred to as being a discrete random variable. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

403)

i. A random variable may be either discrete or continuous. ii. If Unique Buying Services has 100 employees, there might be 0, 1, 2, 3 up to 100 employees absent on Monday. In this case, the day of the week is the random variable. iii. A discrete variable may assume fractional or decimal values, but they must have distance between them. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

404)

What kind of distribution are the binomial and Poisson distributions? A) Discrete B) Continuous C) Both discrete and continuous D) Neither discrete nor continuous

405)

The weight of an offensive linesman may be 205.15 pounds, 210.23 pounds, 225.05 pounds or 219.14 pounds. What is this an illustration of? A) Continuous random variable B) Discrete random variable C) Complement rule D) Probability distribution

406)

If the variance of a probability was computed to be 3.6 grams, what is the standard deviation? A) 0.6 B) 1.9 C) 6.0 D) 12.96

407)

The probabilities and the number of automobiles lined up at a Lakeside Olds at opening time (7:30 A.M.) for service are: Number

Probability

0.05

0.30

0.40

0.25

407.1) On a typical day, how many automobiles should Lakeside Olds expect to be lined up at

opening? A) 10.00 B) 1.00 C) 2.85 D) 1.96

407.2) On a typical day, what is the variance of the number of automobiles that Lakeside Olds

should expect to be lined up at opening? A) 0.0576 B) 2.85 C) 0.7275 D) 0.1 E) 0.5293

407.3) On a typical day, what is the standard deviation of the number of cars that Lakeside Olds

can expect to be lined up at opening? A) 1.96 B) 2.85 C) 0.7275 D) 0.2400 E) 0.8529

408)

Belk Department Store is having a special sale this weekend. Customers charging purchases of more than $50 to the Belk credit card will be given a special Belk lottery card. The customer will scratch the card, which will indicate the amount to be taken off the total amount of purchase. Listed below is the amount of the prize and the percent of the time that amount will be deducted from the total amount of the purchase Prize amount

Probability

$10

0.5

0.4

0.08

100

0.02

Determine the mean and standard deviation of the prize amount. A) Mean is $21, standard deviation is $16.09 B) Mean is $21, standard deviation is $710.50 C) Mean is $20, standard deviation is $25.00 D) Mean is $20, standard deviation is $26.66 E) Mean is $46.25, standard deviation is $710.50

409)

The information below is the number of daily emergency assists made to skiers by the volunteer ski team at Alpine Ski Lodge for the last 50 days. To explain, there were 22 days on which there were 2 emergency assists and 9 days on which there were 3 emergency assists. Number of calls

Frequency

Total

409.1) Convert this information to a probability distribution, and determine the mean number of

assists per day. A) 1.56 B) 1.7 C) 1.66 D) 1.76 E) 1.77

409.2) Convert this information to a probability distribution, and determine the standard

deviation number of assists per day. A) 1.0 B) 1.7 C) 1.66 D) 1.76 E) 1.77

410)

Let X represent the number of children in a Canadian household. The probability distribution of X is as follows: x

p ( x )

.25

.42

.17

.15

.01

Determine the expected number of children in a randomly selected Canadian household. A) 2.25 B) 2.0 C) 2.5 D) 2.75 E) 3.0

411)

On a very hot summer day, 5 percent of the production employees at Midland States Steel are absent from work. The production employees are to be selected at random for a special in-depth study on absenteeism. What is the probability of selecting 10 production employees at random on a hot summer day and finding that none of them are absent? A) 0.002 B) 0.344 C) 0.599 D) 0.100 E) 0.630

412)

Sponsors of a local charity decided to attract wealthy patrons to its $500-a-plate dinner by allowing each patron to buy a set of 20 tickets for the gaming tables. The chance of winning a prize for each of the 20 plays is 50-50. If you bought 20 tickets, what is the chance of winning 15 or more prizes? A) 0.250 B) 0.021 C) 0.006 D) 0.750 E) 0.50

413)

In a large metropolitan area, past records revealed that 30 percent of all the high school graduates go to college. From 20 graduates selected at random, what is the probability that exactly 8 will go to college? A) 0.114 B) 0.887 C) 0.400 D) 0.231

414)

Which of the following is NOT a characteristic of a binomial probability distribution? A) Each outcome is mutually exclusive. B) Each trial is independent. C) Probability of success remains constant from trial to trial. D) Each outcome results from two trials.

415)

What must you know to develop a binomial probability distribution? A) Probability of success B) Number of trials C) Number of successes D) Probability of success and the number of trials E) Probability of success and the number of successes

416)

Chances are 50-50 that a newborn baby will be a girl. For families with five children, what is the probability that all the children are girls? A) 0.100 B) 0.031 C) 0.001 D) 0.250

417)

A true-false test consists of six questions. If you guess the answer to each question, what is the probability of getting all six questions correct? A) 0 B) 0.016 C) 0.062 D) 0.250

418)

i. For a binomial distribution, each trial has a known number of successes. For example, a four question multiple-choice test can only have zero, one, two, three and four successes (number correct). ii. To construct a binomial probability distribution, the number of trials and the probability of success must be known. iii. A binomial distribution has a characteristic that the trials are independent, which means that the outcome of one trial does not affect the outcome of any other trial. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

419)

i. A binomial distribution has a characteristic that an outcome of an experiment is classified into one of two mutually exclusive categories (a success or a failure). ii. A binomial distribution has the characteristic that the probability of a success stays the same for each trial, but the probability of a failure varies from trial to trial. iii. The mean of a binomial probability distribution can be determined by multiplying the probability of a failure by the number of trials. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

420)

i. A binomial distribution is a continuous probability distribution. ii. To construct a binomial distribution, it is necessary to know the total number of trials and the probability of success on each trial. iii. If the probability of success remains the same, but n increases, the shape of the binomial distribution becomes more symmetrical. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

421)

Which one of the following is NOT a condition of the binomial distribution? A) Independent trials B) Only two outcomes C) Probability of success remains constant from trial to trial D) At least 10 observations

422)

i. A binomial distribution is a discrete probability distribution. ii. To construct a binomial distribution, it is necessary to know the total number of trials and the probability of success on each trial. iii. If the probability of success remains the same, but n increases, the shape of the binomial distribution becomes more symmetrical. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

423)

Which is true for a binomial distribution? A) There are three or more possible outcomes. B) Probability of success remains the same from trial to trial. C) Value of p is equal to 1.50. D) Value of p is equal to 0.5.

424)

i. The mean of a binomial distribution is the product of the probability of success and the number of repetitions of the experiment. ii. The binomial probability distribution is always negatively skewed. iii. A binomial distribution has the characteristic that the probability of a success stays the same for each trial, but the probability of a failure varies from trial to trial. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

425)

A true-false test consists of five questions.

425.1) If you guess the answer to each question, what is the probability of getting all five

questions correct? A) 0% B) 3.1% C) 6.2% D) 100%

425.2) A true-false test consists of five questions. If you guess the answer to each question, what

is the probability of getting three or more questions correct? A) 15.6% B) 31.25% C) 50% D) 100%

426)

A multiple-choice test consists of five questions, each with A-E answers.

426.1) If you guess the answer to each question, what is the probability of getting three or more

questions correct? A) 5.1% B) 0.64% C) 0.032% D) 5.7%

426.2) If you guess the answer to each question, what is the probability of getting four or more

questions correct? A) 5.1% B) 6.4% C) 0.032% D) Less than 1%

427)

If you guess the answer to each question, how many questions can you expect to get correct? A) 1 B) 2 C) 3 D) 1.2

428)

David's gasoline station offers 4 cents off per litre if the customer pays in cash and does not use a credit card. Past evidence indicates that 40% of all customers pay in cash. During a one-hour period twenty-five customers buy gasoline at this station.

428.1) What is the probability that at least ten pay in cash? A) 0.416 B) 0.575 C) 0.586 D) 0.425

428.2) What is the probability that no more than twenty pay in cash? A) 0.0 B) 0.1 C) 0.9 D) 1.0

428.3) What is the probability that more than ten and less than fifteen customers pay in cash? A) 0.541 B) 0.401 C) 0.380 D) 0.562

428.4) This situation is an example of what type of discrete probability distribution? A) Continuous probability distribution B) Poisson probability distribution C) Binomial probability distribution D) Hypergeometric probability distribution

429)

Affirmative action commitments by industrial organizations have led to an increase in the number of women in executive positions. Satellite Office Systems has vacancies for two executives that it will fill from among four women and six men.

429.1) This is an example of what type of probability distribution? A) Continuous probability distribution B) Poisson probability distribution C) Binomial probability distribution D) Hypergeometric probability distribution

429.2) What is the probability that no woman is selected? A) 1/5 B) 1/3 C) 2/15 D) 8/15

429.3) What is the probability that at least one woman is selected? A) 8/15 B) 3/5 C) 2/3 D) 3/4

429.4) What is the probability that exactly one woman is selected? A) 8/15 = 0.533 B) 3/5 = 0.60 C) 2/3 = 0.667 D) 3/4 = 0.75

430)

An insurance agent has appointments with four prospective clients tomorrow. From past experience the agent knows that the probability of making a sale on any appointment is 1 out of 5. Using the rules of probability, what is the likelihood that the agent will sell a policy to 3 of the 4 prospective clients? A) 0.250 B) 0.500 C) 0.410 D) 0.026

431)

In a binomial distribution where n = 900 and p = 1/3, determine the mean and standard deviation. A) 2,700, 200 B) 2,700, 14.14 C) 300, 200 D) 300, 14.14

432)

If n = 100 and p = 1/5, determine the mean and standard deviation of this binomial distribution. A) 20, 16 B) 20, 4 C) 500, 200 D) 200, 16

433)

Elly's hot dog emporium is famous for its chilidogs. Some customers order the hot dogs with hot peppers, while many do not care for that added bit of zest. Elly's latest sales indicate that 30% of the customers ordering their chilidogs order it with hot peppers. Suppose 18 customers are selected at random.

433.1) What is the probability that exactly ten customers will ask for hot peppers? A) 0.015 B) 0.15 C) 0.708 D) 0.00

433.2) What is the probability that between two and six people inclusive want hot peppers? A) 0.015 B) 0.15 C) 0.708 D) 0.807

433.3) What is the probability that fifteen or more customers will want hot peppers? A) 0.015 B) 0.15 C) 0.708 D) 0.807 E) 0.00

433.4) What is the probability that exactly nine customers will ask for hot peppers? A) 0.0000 B) 0.708 C) 0.015 D) 0.5 E) 0.039

433.5) What is the probability that between two and five people inclusive want hot peppers? A) 0.0000 B) 0.708 C) 0.015 D) 0.52 E) 0.80

433.6) What is the probability that sixteen or more customers will want hot peppers? A) 0.0000 B) 0.708 C) 0.015 D) 0.5 E) 0.80

433.7) This situation is an example of what type of distribution? A) Binomial distribution B) Hypergeometric distribution C) Poisson distribution D) Chi-squared distribution

434)

When surveyed for brand recognition, 98% of consumers recognize Coke. A new survey of 800 randomly selected consumers is to be conducted. For such a group of 800, determine the mean and standard deviation for the number who recognize the Coke brand name.

434.1) Considering as unusual a result that differs from the mean by more than two standard

deviations, it is/is not unusual to get 775 consumers who recognize the Coke brand name? A) 16, 3.96, is not B) 16, 16, is C) 784, 3.96, is D) 874, 16, is not

434.2) Considering as unusual a result that differs from the mean by more than two standard

deviations, it is/is not unusual to get 790 consumers who recognize the Coke brand name? A) 16, 3.96, is not B) 16, 16, is C) 784, 3.96, is not D) 784, 3.96, is

434.3) Considering as unusual a result that differs from the mean by more than two standard

deviations, it is/is not unusual to get 775 consumers who recognize the Coke brand name? A) 96, 9, is B) 784, 3.96, is C) 784, 9, is not D) 96, 39.6, is not E) 396, 78.4, is not

435)

Sixty percent of the customers of a fast food chain order a hamburger, French fries and a drink. If a random sample of 15 cash register receipts is selected:

435.1) What is the probability that 10 will show that the above three food items were ordered? A) .1859 B) 0.7827 C) 0.2066 D) 0.2173 E) 0.4032

435.2) What is the probability that 10 or more will show that the above three food items were

ordered? A) 1.000 B) 0.7827 C) 0.9095 D) 0.4032 E) 0.0905

435.3) What is the probability that less than 10 will show that the above three food items were

ordered? A) 1.000 B) 0.7827 C) 0.9095 D) 0.5968 E) 0.0905

435.4) What is the probability that 10 or more will show that the above three food items were

ordered? A) 1,000 B) 0.186 C) 0.403 D) 0.000

436)

Judging from recent experience, 5 percent of the computer keyboards produced by an automatic, high-speed machine are defective.

436.1) If six keyboards are randomly selected, what is the probability that none of the keyboards

are defective? A) 0.167 B) 0.735 C) 0.500 D) 1.00 E) 0.2321

436.2) If six keyboards are randomly selected, what is the probability that more than 3 of the

keyboards are defective? A) 0.167 B) 0.0001 C) 0.0000 D) 1.00 E) 0.2321

436.3) What is the probability that out of six keyboards selected at random, exactly zero

keyboards will be defective? A) 0.001 B) 0.167 C) 0.735 D) 0.500

437)

Carlson Jewelers permits the return of their diamond wedding rings, provided the return occurs within two weeks of the purchase date. Their records reveal that 10 percent of the diamond wedding rings are returned. Five different customers buy five rings.

437.1) What is the probability that all will be returned? A) 0.00250 B) 0.59049 C) 0.00590 D) 0.00045 E) 0.00001

437.2) What is the probability that none will be returned? A) 0.250 B) 0.073 C) 0.590 D) 0.500 E) 0.372

438)

i. As a general rule of thumb, if the items selected for a sample are not replaced and the sample size is less than 5 percent of the population, the binomial distribution can be used to approximate the hypergeometric distribution. ii. If the probability of success does not remain the same from trial to trial when sampling is done without replacement, the hypergeometric distribution should be applied. iii. In the hypergeometric distribution the probability of a success is not the same on each trail. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

439)

The marketing department of a nationally known cereal maker plans to conduct a national survey to find out whether or not consumers of flake cereals can distinguish one of their favorite flake cereals. To test the questionnaire and procedure to be used, eight persons were asked to cooperate in an experiment. Five very small bowls of flake cereals were placed in front of a person. The bowls were labeled A, B, C, D, and E. The person was informed that only one bowl contained his or her favorite flake cereal. Suppose that the eight persons in the experiment were unable to identify their favorite cereal and just guessed which bowl it was in. What is the probability that none of the eight guessed correctly? A) 0.168 B) 0.009 C) 0.788 D) 0.125

440)

In which of the following discrete distribution does the probability of a success vary from one trial to the next? A) Binomial B) Poisson C) Hypergeometric D) Binomial, Poisson and Hypergeometric E) Poisson and Hypergeometric

441)

Which of the following is a requirement for use of the hypergeometric distribution? A) Only 2 possible outcomes. B) Trials are independent. C) Probability of a success is greater than 1.0. D) Only 2 possible outcomes and trial are independent.

442)

An insurance agent has appointments with four prospective clients tomorrow. From past experience the agent knows that the probability of making a sale on any appointment is 1 out of 5. Using the rules of probability, what is the likelihood that the agent will sell a policy to at least 3 of the 4 prospective clients? A) 0.0016 B) 0.4096 C) 0.0272 D) 0.0256

443)

Sweetwater & Associates write weekend trip insurance at a very nominal charge. Records show that the probability that a motorist will have an accident during the weekend and file a claim is 0.00555.

443.1) Suppose they wrote 400 policies for the coming weekend, approximately how many

claims could they expect to be filed? A) 200 B) 20 C) 2 D) 0.2

443.2) Suppose they wrote 900 policies for the coming weekend, how many claims could they

expect to be filed? A) We have been given insufficient information to make such a prediction. B) Sweetwater & Associates would normally expect to have 18 claims filed. C) Sweetwater & Associates would normally expect to have 2 claims filed. D) Sweetwater & Associates would expect to have five claims filed.

443.3) Suppose they wrote 400 policies for the coming weekend, what is the probability that

exactly two claims will be filed? A) 0.8187 B) 0.2500 C) 0.2683 D) 0.0001

444)

445)

How is a Poisson distribution skewed? A) Positively B) Negatively C) Symmetrical

The production department has installed a new spray machine to paint automobile doors. As is common with most spray guns, unsightly blemishes often appear because of improper mixture or other problems. A worker counted the number of blemishes on each door. Most doors had no blemishes; a few had one; a very few had two, and so on. The average number was 0.5 per door. The distribution of blemishes followed the Poisson distribution. Out of 10,000 doors painted, about how many would have no blemishes? A) About 6,065 B) About 3,935 C) About 5,000 D) About 500

446)

A manufacturer of headache medicine claims it is 70 percent effective within a few minutes. That is, out of every 100 users 70 get relief within a few minutes. A group of 12 patients are given the medicine. If the claim is true, what is the probability that 8 have relief within a few minutes? A) 0.001 B) 0.168 C) 0.667 D) 0.231

447)

A hybrid-grower is experiencing trouble with corn borers. A random check of 5,000 ears revealed the following: many of the ears contained no borers. Some ears had one borer; a few had two borers; and so on. The distribution of the number of borers per ear approximated the Poisson distribution. The grower counted 3,500 borers in the 5,000 ears. What is the probability that an ear of corn selected at random will contain no borers? A) 0.3476 B) 0.4966 C) 1.000 D) 0.0631

448)

A machine shop has 100 drill presses and other machines in constant use. The probability that a machine will become inoperative during a given day is 0.0555. During some days no machines are inoperative, but during some days, one, two, three, or more are broken down. What is the probability that fewer than two machines will be inoperative during a particular day? A) 0.0228 B) 0.1637 C) 0.8187 D) 0.02546

449)

What is the only variable in the Poisson probability formula? A) π B) x C) e D) P

450)

In a Poisson distribution the mean is equal to A) nπ. B) -x C) e . D) E) zero.

451)

i. The random variable for a Poisson probability distribution is discrete. ii. The Poisson probability distribution is always negatively skewed. iii. The Poisson probability distribution has the same four characteristics as the binomial, but in addition, the probability of a success (π) is small and the number of trials (n) is relatively large. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

452)

A statistics professor finds that on an average she will get five e-mail messages per day from students. Assume the number of messages approximates a Poisson distribution.

452.1) What is the probability that on a randomly selected day she will have no messages? A) 0.0067 B) Zero C) 0.0335 D) Impossible to have no messages

452.2) What is the probability that on a randomly selected day she will have five messages? A) 0.0067 B) 0.875 C) 0.175 D) 1.0

452.3) What is the probability that on a randomly selected day she will have two messages? A) 0.0067 B) 0.0014 C) 0.420 D) 0.084 E) 0.5

453)

If the variance is 3.6 grams, what is the standard deviation? A) 0.0600 B) 1.897 C) 0.6 D) 6.0 E) 1.789

454)

A company is studying the number of daily debit card purchases. There were 20 purchases and the probability of a debit card purchase is 0.5. Of the 20 purchases, what is the expected value of the number of debit card purchases? A) 4 B) 6 C) 8 D) 10 E) 12

455)

(i) A probability distribution relates the expected outcomes of an experiment to the probability of each one occurring. (ii) The probability of all events in a probability distribution must sum to one. (iii) An infinite population consists of a fixed number of individuals, objects, or measurements. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

456)

(i) A probability distribution relates the expected outcomes of an experiment to the probability of each one occurring. (ii) The probability of all events in a probability distribution must sum to one. (iii) A finite population consists of a fixed number of individuals, objects, or measurements. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

457)

(i) A continuous random variable can assume only a certain number of separated values. (ii) The sum of the probabilities of the mutually exclusive outcomes of a probability distribution must equal one. (iii) In a binomial experiment, the probability of a failure equals the probability of success. A) (i), (ii) and (iii) are all correct statements. B) (i) is a correct statement but not (ii) and (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) is a correct statement but not (i) and (iii). E) (i), (ii) and (iii) are all false statements.

458)

(i) A discrete random variable can assume only a certain number of separated values. (ii) The sum of the probabilities of the mutually exclusive outcomes of a probability distribution must equal one. (iii) In a binomial experiment, the probability of a failure equals the probability of success. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

459)

(i) A continuous random variable can assume one of an infinite number of values within a specific range. (ii) The sum of the probabilities of the mutually exclusive outcomes of a probability distribution must equal one. (iii) In a binomial experiment, the probability of a failure equals (1 - probability of success). A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

460)

When a household is randomly selected, the probability distribution for the number x of cars owned is as described in the accompanying table. x

P ( x )

0.011

0.394

0.380

0.215

Find the mean and standard deviation of the probability distribution. A) 0.0000, 0.0000 B) 1.75, 0.859 C) 1.75, 0.895 D) 1.97, 0.853 E) 1.799, 0.783

461)

If your college hires the next four employees without regard to gender, and the pool of applicants is large with an equal number of men and women, then the probability distribution for the number x of women hired is described in the accompanying table. x

P ( x )

0.0625

0.2500

0.3750

0.2500

0.0625

Find the mean and standard deviation of the probability distribution. A) 2.00, 2.0000 B) 1.75, 0.859 C) 1.75, 0.895 D) 1.57, 1.0 E) 2.0, 1.0

462)

(i) A binomial probability distribution approaches a greater degree of symmetry as probability of success remains constant and the number of trials becomes larger or greater. (ii) In a binomial experiment, the probability of a failure equals the probability of success. (iii) In a binomial experiment, probability of success or failure remains constant from one trial to another. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

463)

(i) A binomial probability distribution approaches a greater degree of symmetry as probability of success remains constant and the number of trials becomes larger or greater. (ii) In a binomial experiment, the probability of a failure equals (1 - probability of success). (iii) In a binomial experiment, probability of success or failure remains constant from one trial to another. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

464)

(i) A binomial probability distribution approaches a greater degree of symmetry as probability of success remains constant and the number of trials becomes larger or greater. (ii) In a binomial experiment, the probability of a failure equals (1 - probability of success). (iii) In a binomial experiment, probability of success or failure changes from one trial to another. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

(i) If π = 1/3 and n = 900, the mean of this binomial distribution is 300. (ii) If n = 900 and π = 1/3, the variance of this binomial distribution is 200. (iii) If π = 1/5 and n = 100, the standard deviation of this binomial distribution is 16. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

465)

(i) If π = 1/3 and n = 900, the mean of this binomial distribution is 300. (ii) If n = 900 and π = 1/3, the variance of this binomial distribution is 200. (iii) If π = 1/5 and n = 100, the standard deviation of this binomial distribution is four. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

466)

467)

(i) To construct a binomial distribution we need to know the total number of trials and the probability of a success. (ii) If n = 900 and π = 1/3, the variance of this binomial distribution is 200. (iii) If π = 1/5 and n = 100, the standard deviation of this binomial distribution is 20. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

468)

(i) To construct a binomial distribution we need to know the total number of trials and the probability of a success. (ii) If n = 900 and π = 1/3, the variance of this binomial distribution is 200. (iii) If π = 1/5 and n = 100, the standard deviation of this binomial distribution is four. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

469)

In a large metropolitan area, past records revealed that 30 percent of all the high school graduates go to college. From 20 graduates selected at random, approximately how many will go to college? A) 3 B) 4 C) 5 D) 6 E) 7

470)

In a large metropolitan area, past records revealed that 30 percent of all the high school graduates go to college. From 10 graduates selected at random, calculate the probability that none will go to college. A) 0.028% B) 82% C) 28% D) 8.2% E) 2.8%

471)

A marketing solutions poll of mutual funds and fund owners asked fund owners what action they took after the September 11th2001 market drop. Sixteen percent of respondents said they bought more funds. If 600 fund owners were polled, calculate the mean and standard deviation of the number of respondents who bought more funds. Considering as unusual a result that differs from the mean by more than two standard deviations, it (___ (is/is not) ___) unusual that in one of these polls of 600 fund owners, 100 respondents bought more mutual funds. A) 96, 9, is not B) 96, 8, is C) 96, 9, is D) 95, 8, is not E) 95, 8, is

472)

Let X represent the number of children in a Canadian household. The probability distribution of X is as follows: x

P ( x )

.25

.42

.17

.15

.01

What is the probability that a randomly selected Canadian household will have more than 3 children? What is the expected number of children in a Canadian household? A) 0.7311, 2 B) 0.3711, 3.2 C) 0.16, 2.25 D) 0.16, 3.2

473)

(i) A random variable with a Poisson distribution has one of two mutually exclusive values. (ii) For the hypergeometric distribution there are only 2 possible outcomes. (iii) In the hypergeometric distribution the probability of a success is the same on each trail. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (ii) are correct statements but not (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

474)

(i) A random variable with a Poisson distribution has one of three mutually exclusive values. (ii) For the hypergeometric distribution there are only 2 possible outcomes. (iii) In the hypergeometric distribution the probability of a success is not the same on each trail. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

475)

(i) A random variable with a Poisson distribution has one of two mutually exclusive values. (ii) For the hypergeometric distribution there are only 2 possible outcomes. (iii) In the hypergeometric distribution the probability of a success is not the same on each trail. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

476)

In a Poisson distribution each trail is independent.

(i) The binomial distribution and the Poisson distribution have two possible experimental outcomes. (ii) The Poisson distribution or, the law of improbable events, has negatively skewed shape. (iii) In a Poisson distribution each trail is dependent on the others. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

477)

The arrival of customers at a service desk follows a Poisson distribution. If they arrive at the rate of two every five minutes, what is the probability that no customers arrive in a fiveminute period? A) 0.7311 B) 0.3711 C) 0.1353 D) 0.16

478)

The arrival of customers at a service desk follows a Poisson distribution. If they arrive at the rate of four every five minutes, what is the probability that more than four customers arrive in a five minute period? A) 0.7311 B) 0.3711 C) 0.5 D) 0.16

479)

(i) The binomial distribution and the Poisson distribution have two possible experimental outcomes. (ii) The Poisson distribution or, the law of improbable events, has negatively skewed shape. (iii) In a Poisson distribution each trail is independent. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

480)

A player usually has 3 at bats in baseball game. Let X represent the number of times a player gets on base in a game. For example 60% of the time a player will not get on base in a game and 5% of the time the player will be on base for all 3 at bats in a game. X

P(X)

0.60

0.25

0.10

0.05

480.1) What is the probability a player does not get on base in a game? A) 0.60 B) 0.25 C) 0.10 D) 0.05

480.2) What is the probability a player gets on base only once in a game? A) 0.60 B) 0.25 C) 0.10 D) 0.05

480.3) What is the probability a player gets on base twice in a game? A) 0.60 B) 0.25 C) 0.10 D) 0.05

480.4) What is the probability a player gets on base all 3 times at bat? A) 0.60 B) 0.25 C) 0.10 D) 0.05

480.5) What is the probability a player gets on base at least once in a game? A) 0.60 B) 0.40 C) 0.25 D) 0.01

480.6) What is the probability a player gets on at least twice in a game? A) 0.60 B) 0.25 C) 0.15 D) 0.10

480.7) What is the probability a player gets on base no more than once in a game? A) 1.0 B) 0.85 C) 0.60 D) 0.25

480.8) What is the expected number of time a player will get on base in a game? A) 0.0 B) 0.50 C) 0.60 D) 2.0

480.9) What is the standard deviation for the number of times a player will get on base in a

game? A) B) C) D)

0.60 0.74 0.86 1.0

481)

The probability of getting a "hit" in baseball is approximately 0.30. If a sample of the next 5 batters are taken:

481.1) What is the probability that all 5 batters get a hit? A) 0.00 B) 0.03 C) 0.17 D) 0.36

481.2) What is the probability that none of the batters get a hit? A) 0.00 B) 0.03 C) 0.17 D) 0.36

481.3) What is the probability that 1 of the batters get a hit? A) 0.00 B) 0.03 C) 0.17 D) 0.36

481.4) What is the probability that at least 1 of the batters get a hit? A) 0.00 B) 0.53 C) 0.83 D) 1

481.5) What is the probability that at least 2 of the batters get a hit? A) 0.00 B) 0.53 C) 0.47 D) 1

481.6) What is the probability that at most 1 of the batters get a hit? A) 0.00 B) 0.53 C) 0.83 D) 1

481.7) What is the expected number of hits? A) 1.0 B) 1.02 C) 1.05 D) 1.5

481.8) What is the standard deviation number of hits? A) 1.0 B) 1.02 C) 1.05 D) 1.5

482)

In the minor leagues the average number of hits per game for a player is 2.

482.1) What is the probability that a player gets 3 hits in a game? A) 0.135 B) 0.271 C) 0.180 D) 0.271

482.2) What is the probability that a player does not get a hit in a game? A) 0.135 B) 0.271 C) 0.180 D) 0.271

482.3) What is the probability that a player gets at least 1 hit in a game? A) 0.180 B) 0.271 C) 0.406 D) 0.865

482.4) What is the probability that a player gets at most 1 hit in a game? A) 0.180 B) 0.271 C) 0.406 D) 0.451

Answer Key Test name: chapter 5 394) A 395) D 396) A 397) B 398) B 399) A 400) C 401) A 402) Section Break 402.1) C 402.2) C 402.3) A 403) D 404) B 405) C 406) A 407) A 408) B 409) Section Break 409.1) C 409.2) C 409.3) E 410) A 411) Section Break 411.1) B 411.2) A 412) A 413) C 414) B 415) A 416) D 417) D 418) B 419) B 420) A 421) B 422) D

423) D 424) A 425) B 426) B 427) Section Break 427.1) A 427.2) A 428) Section Break 428.1) D 428.2) D 429) A 430) Section Break 430.1) B 430.2) D 430.3) C 430.4) C 431) Section Break 431.1) D 431.2) B 431.3) C 431.4) A 432) D 433) D 434) B 435) Section Break 435.1) A 435.2) C 435.3) E 435.4) E 435.5) D 435.6) A 435.7) A 436) Section Break 436.1) C 436.2) C 436.3) B 437) Section Break 437.1) A 437.2) D 437.3) D

437.4) C 438) Section Break 438.1) B 438.2) B 438.3) C 439) Section Break 439.1) E 439.2) C 440) A 441) A 442) C 443) A 444) C 445) Section Break 445.1) C 445.2) D 445.3) C 446) A 447) A 448) D 449) B 450) A 451) B 452) A 453) C 454) Section Break 454.1) A 454.2) C 454.3) D 455) B 456) D 457) C 458) A 459) D 460) C 461) A 462) E 463) E 464) C 465) A

466) C 467) C 468) A 469) C 470) A 471) D 472) E 473) A 474) C 475) C 476) D 477) A 478) B 479) C 480) B 481) C 482) Section Break 482.1) A 482.2) B 482.3) C 482.4) D 482.5) B 482.6) C 482.7) B 482.8) C 482.9) C 483) Section Break 483.1) A 483.2) C 483.3) D 483.4) C 483.5) C 483.6) B 483.7) D 483.8) B 484) Section Break 484.1) C 484.2) A 484.3) D 484.4) C

Student name:__________ 483)

i. The Empirical Rule of probability can be applied to the uniform probability distribution. ii. Areas within a continuous probability distribution represent probabilities. iii. The total area within a continuous probability distribution is equal to 1. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

484)

i. The total area within any continuous probability distribution is equal to 1.00. ii. For any continuous probability distribution, the probability, P(x), of any value of the random variable, X, can be computed. iii. For any discrete probability distribution, the probability, P(x), of any value of the random variable, X, can be computed. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

485)

i. Areas within a continuous probability distribution represent probabilities. ii. The total area within any continuous probability distribution is equal to 1.00. iii. For any discrete probability distribution, the probability, P(x), of any value of the random variable, X, can be computed. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

486)

i. For any uniform probability distribution, the mean and standard deviation can be computed by knowing the maximum and minimum values of the random variable. ii. In a uniform probability distribution, P(x) is constant between the distribution's minimum and maximum values. iii. The uniform probability distribution's shape is a rectangle. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

487)

i. Areas within a continuous probability distribution represent probabilities. ii. The Empirical Rule of probability can be applied to the uniform probability distribution. iii. The total area within a continuous probability distribution is equal to 100. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

488)

i. The uniform probability distribution is symmetric about the mean and median. ii. The uniform probability distribution's shape is a rectangle. iii. In a uniform probability distribution, P(x) is constant between the distribution's minimum and maximum values. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

489)

i. The uniform probability distribution's standard deviation is proportional to the distribution's range. ii. The uniform probability distribution is symmetric about the mode. iii. For a uniform probability distribution, the probability of any event is equal to 1/(b - a). A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

490)

i. The uniform probability distribution's shape is a rectangle. ii. The uniform probability distribution is symmetric about the mode. iii. In a uniform probability distribution, P(x) is constant between the distribution's minimum and maximum values. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and, (iii) are correct statements but not (ii). D) (ii) and, (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

491)

i. In a uniform probability distribution, P(x) is constant between the distribution's minimum and maximum values. ii. For a uniform probability distribution, the probability of any event is equal to 1/(b-a). iii. The uniform probability distribution is symmetric about the mode. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

492)

The shape of any uniform probability distribution is: A) Negatively skewed B) Positively skewed C) Rectangular D) Bell shaped

493)

The mean of any uniform probability distribution is: A) (b - a)/2 B) (a + b)/2 C) D) nπ

494)

The standard deviation of any uniform probability distribution is: A) (b - a)/2 B) n(1 - π) C) D)

495)

A major credit card company has determined that customers charge between $100 and $1,100 per month.

495.1) Given that the average monthly amount charged is uniformly distributed, what is the

standard deviation of the monthly amount charged? A) 298.67 B) 275.57 C) 267.88 D) 288.67

495.2) Given that the average monthly amount charged is uniformly distributed, what percent of

monthly charges are between $600 and $889? A) 28.9% B) 20.8% C) 26.2% D) 29.3%

495.3) Given that the average monthly amount charged is uniformly distributed, what is the

probability that a person charges less than $200 per month? A) 5% B) 10% C) 15% D) 20%

496)

A financial advising company has determined that the price-to-earnings ratios for 20 randomly selected publicly traded companies range between 0.9 and 2.9.

496.1) Given that the price-to-earnings ratios are uniformly distributed, what percent of price-to-

earnings ratios are between 1.90 and 2.48? A) 19% B) 20% C) 26% D) 29%

496.2) Given that the price-to-earnings ratios are uniformly distributed, what is the average

price-to-earnings ratio? A) 0.9 B) 1.9 C) 2.9 D) 3.8

497)

The upper and lower limits of a uniform probability distribution are A) positive and negative infinity. B) plus and minus three standard deviations. C) 0 and 1. D) the maximum and minimum values of the random variable.

498)

What is an important similarity between the uniform and normal probability distributions? A) The mean, median and mode are all equal. B) The mean and median are equal. C) They are negatively skewed. D) About 68% of all observations are within one standard deviation of the mean.

499)

i. Asymptotic, means that the normal curve gets closer and closer to the X-axis but never actually touches it. ii. When referring to the normal probability function, there is not just one of them; there is a "family" of them. iii. Some normal probability distributions have equal arithmetic means, but their standard deviations may be different. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

i. The mean of a normal distribution is represented by ς. ii. Some normal probability distributions have equal arithmetic means, but their standard deviations may be different. A) (i) and (ii), are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are both false statements.

500)

501)

i. The normal curve falls off smoothly in either direction from the central value. Since it is asymptotic, the curve gets closer and closer to the X-axis, but never actually touches it. ii. The mean ( µ) divides the normal curve into two identical halves. iii. The number of different normal distributions is unlimited. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

502)

i. Asymptotic, means that the normal curve gets closer and closer to the X-axis but never actually touches it. ii. When referring to the normal probability function, there is not just one of them; there is a "family" of them. iii. Some normal probability distributions have different arithmetic means and different standard deviations. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

503)

Which of the following is true in a normal distribution? A) Mean equals the mode and the median B) Mode equals the median C) Mean divides the distribution into two equal parts D) Mean equals the mode and the median and Mean divides the distribution into two equal parts

504)

Which of the following is NOT a characteristic of the normal probability distribution? A) Positively-skewed B) Bell-shaped C) Symmetrical D) Asymptotic

505)

A random variable from an experiment where outcomes are normally distributed can have A) any value between -∞ and +∞ B) only a few discrete values C) a mean of 0 and a standard deviation of 1 D) no values

506)

The total area of a normal probability distribution is A) between -3.0 and 3.0. B) 1.00. C) dependent on a value of 'z'. D) approximated by the binomial distribution.

507)

Which of the following is NOT true regarding the normal distribution? A) Mean, median and mode are all equal B) It has a single peak C) It is symmetrical D) The points of the curve meet the X-axis at z = -3 and z = 3

508)

Two normal distributions are compared. One has a mean of 10 and a standard deviation of 10. The second normal distribution has a mean of 10 and a standard deviation of 2. Which of the following is true? A) The locations of the distributions are different. B) The distributions are from two different families. C) The dispersions of the distributions are different. D) The dispersions of the distributions are the same.

i. A z-score is the distance between a selected value ( X)and the population mean ( μ) divided by the population standard deviation (ς). ii. The standard normal distribution is a special normal distribution with a mean of 0 and a standard deviation of 1. iii. A computed z for X values to the right of the mean is negative. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

509)

i. In terms of a formula the standardized value of z is found by z = ( X - µ)/ς. ii. The standard normal distribution is a special normal distribution with a mean of 0 and a standard deviation of 1. iii. A computed z for X values to the right of the mean is positive. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

510)

i. In terms of a formula the standardized value of z is found by z = ( X - µ)/ς. ii. The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of less than 10. iii. A computed z for X values to the left of the mean is positive. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

511)

512)

The mean of a normally distributed group of weekly incomes of a large group of executives is $1,000 and the standard deviation is $100. What is the z-score for an income of $1,100? A) 1.00 B) 2.00 C) 1.683 D) - 0.90

513)

Tables of normal distribution probabilities are found in many statistics books. These probabilities are calculated from a normal distribution with A) a mean of 1 and a standard deviation of 1. B) a mean of 100 and a standard deviation of 15. C) a mean of 0 and a standard deviation of 15. D) a mean of 0 and a standard deviation of 1.

514)

The standard normal probability distribution is one which has: A) a mean of 1 and any standard deviation. B) any mean and a standard deviation of 1. C) a mean of 0 and any standard deviation. D) a mean of 0 and a standard deviation of 1.

515)

What is the distribution with a mean of 0 and a standard deviation of 1 called? A) Frequency distribution B) z-score C) Standard normal distribution D) Binomial probability distribution

516)

Two competitive brothers, who work in two different industries, were comparing their salaries. Because there is a difference of 4 years in their respective work experience, they decided to compare not their actual salaries but to compare their salaries against their company averages to see who is doing better. The following gives the brother's salaries, companies mean, and standard deviation for each company. Brother

Salary

Tom

84000

75000

7000

Andy

75500

60000

8200

516.1) What is the z-score of Andy's salary? A) - 1.29 B) 1.29 C) - 1.89 D) 1.89

516.2) What is the z-score of Tom's salary? A) -1.29 B) 1.29 C) -1.89 D) 1.89

516.3) Which brother earns a higher salary compared to the rest of their colleagues? A) Tom B) Andy C) They both compare the same when measured against their colleagues D) Unable to determine from the information given

517)

Two business major students, in two different sections of economics, were comparing test scores. The following gives the students' scores, class mean, and standard deviation for each section. Which student scored better compared to the rest of their section?

A) B) C) D)

Section

Score

The student in section A. The student in section B. Both students scored the same. We are unable to determine who did better from the information given.

518)

i. For a normal probability distribution, about 95 percent of the area under normal curve is within plus and minus two standard deviations of the mean and practically all (99.73 percent) of the area under the normal curve is within three standard deviations of the mean. ii. The total area under the normal curve is 100%. iii. The mean of a normal probability distribution is 500 and the standard deviation is 10. About 95 percent of the observations lie between 480 and 520. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

519)

i. For a normal probability distribution, about 95 percent of the area under normal curve is within plus and minus two standard deviations of the mean and practically all (99.73 percent) of the area under the normal curve is within three standard deviations of the mean. ii. The total area under the normal curve is 1. iii. The mean of a normal probability distribution is 500 and the standard deviation is 10. About 68 percent of the observations lie between 480 and 520. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

520)

i. Disaster Airlines determined that the mean number of passengers per flight is 152 with a standard deviation of ten passengers. Practically all flights have between 142 and 162 passengers. ii. The total area under the normal curve is less than 1. iii. The mean of a normal probability distribution is 500 and the standard deviation is 10. About 68 percent of the observations lie between 480 and 520. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

521)

For the normal distribution, the mean plus and minus 1.96 standard deviations will include about what percent of the observations? A) 50% B) 99.7% C) 95% D) 68%

522)

What is the area under the normal curve between z = -1.0 and z = -2.0? A) 0.0228 B) 0.3413 C) 0.1359 D) 0.4772

523)

What is the area under the normal curve between z = 0.0 and z = 2.0? A) 1.0000 B) 0.7408 C) 0.1359 D) 0.4772

524)

What is the proportion of the total area under the normal curve within plus and minus two standard deviations of the mean? A) 68% B) 99.7% C) 34% D) 95%

525)

A new extended-life light bulb has an average service life of 750 hours, with a standard deviation of 50 hours. If the service life of these light bulbs approximates a normal distribution, about what percent of the distribution will be between 600 hours and 900 hours? A) 95% B) 68% C) 34% D) 99.7%

526)

An accelerated life test on a large number of type-D alkaline batteries revealed that the mean life for a particular use before they failed is 19.0 hours. The distribution of the lives approximated a normal distribution. The standard deviation of the distribution was 1.2 hours. About 95.44 percent of the batteries failed between what two values? A) 8.9 and 18.9 B) 12.2 and 14.2 C) 14.1 and 22.1 D) 16.6 and 21.4

527)

The mean of a normal distribution is 400 kg. The standard deviation is 10 kg. What is the area between 415 kg and the mean of 400 kg? A) 0.5000 B) 0.1932 C) 0.4332 D) 0.3413

528)

The distribution of the annual incomes of a group of middle management employees approximated a normal distribution with a mean of $37,200 and a standard deviation of $800. About 68 percent of the incomes lie between what two incomes? A) $30,000 and $40,000 B) $36,400 and $38,000 C) $34,800 and $39,600 D) $35,600 and $38,800

529)

The seasonal output of a new experimental strain of pepper plants was carefully weighed. The mean weight per plant is 15.0 pounds, and the standard deviation of the normally distributed weights is 1.75 pounds. Of the 200 plants in the experiment, how many produced peppers weighing between 13 and 16 pounds? A) 100 B) 118 C) 197 D) 53

530)

A national manufacturer of unattached garages discovered that the distribution of the lengths of time it takes two construction workers to erect the Red Barn model is approximately normally distributed with a mean of 32 hours and a standard deviation of 2 hours. What percent of the garages take between 32 and 34 hours to erect? A) 16.29% B) 76.71% C) 3.14% D) 34.13%

531)

The annual commissions per salesperson employed by a manufacturer of light machinery averaged $40,000 with a standard deviation of $5,000. What percent of the sales persons earn between $32,000 and $42,000? A) 60.06% B) 39.94% C) 34.13% D) 81.66%

532)

The mean of a normal probability distribution is 500 and the standard deviation is 10. About 95 percent of the observations lie between what two values? A) 475 and 525 B) 480 and 520 C) 400 and 600 D) 350 and 650

533)

The employees of Cartwright Manufacturing are awarded efficiency ratings. The distribution of the ratings approximates a normal distribution. The mean is 400, the standard deviation 50. What is the area under the normal curve between 400 and 482? A) 0.5000 B) 0.4495 C) 0.3413 D) 0.4750

534)

A sample of 500 evening students revealed that their annual incomes were normally distributed with a mean income of $50,000 and a standard deviation of $4,000.

534.1) How many students earned between $47,000 and $53,000? A) 137 B) 273 C) 113 D) 387

534.2) How many students earned between $45,000 and $53,000? A) 170 B) 273 C) 334 D) 387

534.3) How many students earned less than $45,000? A) 53 B) 197 C) 303 D) 35

534.4) How many students earned more than $55,000? A) 53 B) 197 C) 303 D) 35

534.5) What is the income that separates the top 25% from the lower 75% of the incomes? A) $2,680 B) $47,320 C) $50,000 D) $52,680

534.6) What is the income that separates the top 5% from the lower 95% of the incomes? A) $43,420 B) $47,320 C) $56,580 D) $52,680

535)

The mean amount of gasoline and services charged by Key Refining Company credit customers is $70 per month. The distribution of amounts spent is approximately normal with a standard deviation of $10. What is the probability of selecting a credit card customer at random and finding the customer charged between $70 and $83? A) 0.1962 B) 0.4032 C) 0.3413 D) 0.4750

536)

What is the area under the normal curve between z = 0.0 and z = 1.79? A) 0.4633 B) 0.0367 C) 0.9599 D) 0.0401

537)

For a standard normal distribution, what is the probability that z is greater than 1.75? A) 0.0401 B) 0.0459 C) 0.4599 D) 0.9599

538)

The mean amount spent by a family of four on food per month is $500 with a standard deviation of $75. Assuming that the food costs are normally distributed, what is the probability that a family spends less than $410 per month? A) 0.2158 B) 0.8750 C) 0.0362 D) 0.1151

539)

The weekly mean income of a group of executives is $1,000 and the standard deviation of this group is $100. The distribution is normal. What percent of the executives have an income of $925 or less? A) About 15% B) About 85% C) About 50% D) About 23%

540)

The weights of cans of fruit are normally distributed with a mean of 1,000 grams and a standard deviation of 50 grams. What percent of the cans weigh 860 grams or less? A) About 1% B) About 84% C) About 0.26% D) About 0.01%

541)

The mean score of a college entrance test is 500; the standard deviation is 75. The scores are normally distributed. What percent of the students scored below 320? A) About 50.82% B) About 34.13% C) About 7.86% D) About 0.82%

542)

A study of a company's practice regarding the payment of invoices revealed that on the average an invoice was paid 20 days after it was received. The standard deviation equaled five days. Assuming that the distribution is normal, what percent of the invoices were paid within 15 days of receipt? A) 15.87% B) 37.91% C) 34.13% D) 86.74%

543)

Ball-Bearings, Inc. produces ball bearings automatically on a Kronar BBX machine. For one of the ball bearings, the mean diameter is set at 20.00 mm (millimetres). The standard deviation of the production over a long period of time was computed to be 0.150 mm. What percent of the ball bearings will have diameters 20.27 mm or more? A) 41.00% B) 12.62% C) 3.59% D) 85.00%

544)

A cola-dispensing machine is set to dispense a mean of 2.02 litres into a container labelled 2 liters. Actual quantities dispensed vary and the amounts are normally distributed with a standard deviation of 0.015 litres. What is the probability a container will have less than 2 litres? A) 0.0918 B) 0.3413 C) 0.1926 D) 0.8741

545)

The driver's seat in most vehicles is set to comfortably fit a person who is at least 159 cm tall. The distribution of heights of adult women is approximately normal with a mean of 161.5 cm and a standard deviation of 6.3 cm. Determine the percentage of women who can be expected to be uncomfortable in the driver's seat of their car without some sort of an adjustment. A) 0.3446. B) 0.1554. C) 0.6554. D) 0.8446

546)

The average score of 100 students taking a statistics final was 70 with a standard deviation of 7.

546.1) Assuming a normal distribution, approximately how many scored 90 or higher? A) 0.4979 B) 0.0021 C) 0.9979 D) 2.86

546.2) Assuming a normal distribution, approximately how many scored less than 60? A) 0.2271 B) 0.3729 C) 0.8929 D) D)-1.14 E) 0.0764

546.3) Assuming a normal distribution, approximately how many scored greater than 65? A) 0.2611 B) 0.2389 C) 0.7611 D) -0.714

547)

The net profit from a certain investment is normally distributed with a mean of $10,000 and a standard deviation of $5,000. The probability that the investor will not have a net loss is: A) 0.4772 B) 0.9544 C) 0.0228 D) 0.9772 E) 1.0

548)

The net profit from a certain investment is normally distributed with a mean of $10,000 and a standard deviation of $5,000. The probability that the investor will have a net loss is: A) 0.4772 B) 0.9544 C) 0.0228 D) 0.9772 E) 1.0

549)

Suppose a tire manufacturer wants to set a mileage guarantee on its new XB 70 tire. Life test revealed that the mean mileage is 47,900 and the standard deviation of the normally distributed distribution of mileage is 2,050 miles. The manufacturer wants to set the guaranteed mileage so that no more than 5 percent of the tires will have to be replaced. What guaranteed mileage should the manufacturer announce? A) 44,528 B) 32,960 C) 49,621 D) 40,922

550)

Past experience of a large manufacturing firm with administering a test to recent college graduates who had applied for a job revealed that the mean test score was 500, and the standard deviation was 50. The distribution of the test scores was normal. Based on this experience, management is considering placing a person whose score is in the upper 6 percent of the distribution directly into a responsible position. What is the lowest score a college graduate must earn to qualify for a responsible position? A) 50 B) 625 C) 460 D) 578

551)

An analysis of the grades on the first test in History 101 revealed that they approximate a normal curve with a mean of 75 and a standard deviation of 8. The instructor wants to award the grade of A to the upper 10 percent of the test grades. What is the dividing point between an A and a B grade? A) 80 B) 85 C) 90 D) 95

552)

Management is considering adopting a bonus system to increase production. One suggestion is to pay a bonus on the highest 5 percent of production based on past experience. Past records indicate that, on the average, 4,000 units of a small assembly are produced during a week. The distribution of the weekly production is approximately normally distributed with a standard deviation of 60 units. If the bonus is paid on the upper 5 percent of production, the bonus will be paid on how many units or more? A) 6,255 B) 5,120 C) 3,196 D) 4,099

553)

For the standard normal distribution, what z-score corresponds with the 85% percentile? A) 0.30 B) 2.05 C) 0.15 D) 1.04

554)

A statistics student receives a grade of 85 on a statistics midterm. If the corresponding zscore equals + 1.5 and the standard deviation equals 7, the average grade on this exam is: A) 74.5 B) 75.4 C) 68.5 D) 76.9

555)

From past history, the scores on a statistics test are normally distributed with a mean of 70% and a standard deviation of 5%.

555.1) To earn an "A" on the test, a student must be in the top 5% of the class. What should a

student score to receive an "A"? A) 80.84 B) 75.49 C) 78.2 D) 76.90

555.2) To earn a "B" on the test, a student must be in the top 15% of the class. What should a

student score to receive a "B"? A) 75.18 B) 75.49 C) 81.48 D) 76.90

555.3) To earn a "C" on the test, a student must be in the top 25% of the class. What should a

student score to receive a "C"? A) 77.21 B) 73.37 C) 73.96 D) 76.90

556)

Bottomline Ink, a forms management company, fills 100 orders a day with a 2% error rate in the completed orders.

556.1) Assume this to be a binomial distribution. What is the mean for this distribution? A) 0.02 B) 1.4 C) 2 D) There is no mean for this type of distribution.

556.2) Assume this to be a binomial distribution. What is the standard deviation for this

distribution? A) 0.02 B) 1.4 C) 2 D) There is no standard deviation for this type of distribution.

556.3) Assume this to be a binomial distribution. What is the probability that there will be more

than 5 order errors in a given day? A) 0.0062 B) 0.4838 C) 0.9838 D) 2.1428

557)

i. A continuity correction compensates for estimating a discrete distribution with a continuous distribution. ii. The binomial can be used to approximate the normal distribution for small sized samples. iii. The binomial may be used to approximate the normal distribution when the probability, p, remains the same from trial to trial. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

558)

What is the value of the continuity correction factor? A) 1.00 B) 0.50 C) 100 D) 1.96

559)

i. A continuity correction compensates for estimating a discrete distribution with a continuous distribution. ii. The normal probability distribution is generally deemed a good approximation for the binomial probability distribution when np and n(1 - p)are both greater than five. iii. When a continuity correction factor is used, its value is 1. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

560)

i. A continuity correction compensates for estimating a discrete distribution with a continuous distribution. ii. The normal probability distribution is generally deemed a good approximation for the binomial probability distribution when np and n(1 - p)are both greater than five. iii. When a continuity correction factor is used, its value is 0.5. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

561)

A new drug has been developed that is found to relieve nasal congestion in 90 percent of those with the condition. The new drug is administered to 300 patients with the condition. What is the probability that more than 265 will be relieved of nasal congestion? A) 0.0916 B) 0.1922 C) 0.8078 D) 0.3078

562)

Tabulation of a strike vote showed that 90% of those voting cast their ballot in favour of strike action. You take a sample of 50 voters. Assume this to be a binomial distribution.

562.1) What is the mean for this distribution? A) 450 B) 90 C) 45 D) There is no mean for this type of distribution

562.2) What is the standard deviation for this distribution? A) 45 B) 4.5 C) 2.12 D) 20.25

562.3) What is the probability that more than 45 of the voters from your sample voted in favour

of strike action? A) 0.50 B) 0.0948 C) 0.5948 D) 0.4052

562.4) What is the probability that fewer than 40 of your sample voters are in favour of strike

action? A) B) C) D)

0.2594 0.4952 0.0048 0.0091

563)

Determine the z-score associated with an area of.1950 from the mean of a normal distribution to that positive z-score. A) 0.41 B) 0.51 C) 0.5 D) 0.01 E) -0.41

564)

Determine the z-score associated with an area of 0.4925 from the mean of a normal distribution to that negative z-score. A) 2.43 B) -2.43 C) -2.4 D) 2.4 E) -2.44

565)

Determine the z-score associated with an area of 0.25 from the mean of a normal distribution to that positive z-score. A) 0.1368 B) 0.70 C) 0.67 D) 0.68 E) 0.69

566)

Determine the z-score associated with an area of 0.48 from the mean of a normal distribution to that positive z-score. A) 2.05 B) 2.06 C) 0.1844 D) 0.1808 E) 2.60

567)

(i) About 95.5% percent of the area under the normal curve is within plus two and minus two standard deviations of the mean. (ii) The normal distribution is a continuous probability distribution. (iii) In a standard normal distribution, µ = 0 and ς = 1. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

568)

(i) About 95.5% percent of the area under the normal curve is within plus three and minus three standard deviations of the mean. (ii) The normal distribution is a continuous probability distribution. (iii) In a standard normal distribution, µ = 0 and ς = 1. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

569)

(i) About 95.5% percent of the area under the normal curve is within plus one and minus one standard deviation of the mean. (ii) The normal distribution is a continuous probability distribution. (iii) In a standard normal distribution µ = 0 and ς = 1. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

570)

(i) The formula to convert any normal distribution to the standard normal distribution is z = (X - µ)/ς (ii) The standardized value measures distance from the mean in units of standard deviation. (iii) The area under a normal curve to the right of a z-score of zero is a proportion of 0.50. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

571)

(i) The formula to convert any normal distribution to the standard normal distribution is z = (X - µ)/ς (ii) The standardized value measures distance from the mean in units of standard deviation. (iii) The area under a normal curve to the right of a z-score of zero is 1. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

572)

(i) The formula to convert any normal distribution to the standard normal distribution is z = (X - µ)/ς (ii) The standardized z value measures distance from the mean in units of standard deviation. (iii) The area under a normal curve to the right of a z-score of -1.0 is a proportion of 0.3413. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

573)

(i) The mean of a normal probability distribution is 60 and the standard deviation is 5. 95.44 percent of observations lie between 50 and 70. (ii) A z-value of -2.00 indicates that corresponding X value lies to the left of the mean. (iii) One of the properties of the normal curve is that it gets closer to the horizontal axis, but never touches it. This property of the normal curve is called asymptotic. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

574)

(i) The mean of a normal probability distribution is 60 and the standard deviation is 5. 95.44 percent of observations lie between 50 and 60. (ii) A z-value of -2.00 indicates that corresponding X value lies to the left of the mean. (iii) One of the properties of the normal curve is that it gets closer to the horizontal axis, but never touches it. This property of the normal curve is called asymptotic. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

575)

(i) The mean of a normal probability distribution is 60 and the standard deviation is 5. 95.44 percent of observations lie between 50 and 75. (ii) A z-value of -2.00 indicates that corresponding X value lies to the left of the mean. (iii) One of the properties of the normal curve is that it gets closer to the horizontal axis, but never touches it. This property of the normal curve is called asymptotic. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

576)

(i) The proportion of the area under a normal curve to the right of z = -1.21 is 0.8869. (ii) The proportion of the area under a normal curve to the left of z = 0.50 is 0.6915. (iii) The proportion of the area under a normal curve to the left of z = -2.10 is 0.0179. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

577)

(i) The proportion of the area under a normal curve to the right of z = -1.21 is 0.8869. (ii) The proportion of the area under a normal curve to the left of z = 0.50 is 0.6941. (iii) The proportion of the area under a normal curve to the left of z = -2.10 is 0.1179. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

578)

(i) The proportion of the area under a normal curve to the right of z = -1.21 is 0.8869. (ii) The proportion of the area under a normal curve to the left of z = 0.50 is 0.1914. (iii) The proportion of the area under a normal curve to the left of z = -2.10 is 0.0179. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

579)

A statistics student receives a grade of 90 on a statistics midterm. If the corresponding zscore equals + 1.5 and the standard deviation equals 7, determine the average grade on this exam. A) 74.0 B) 79.5 C) 74.7 D) 79.3 E) 75.0

580)

A sample of 500 evening students revealed that their annual incomes from employment in industry during the day were normally distributed with a mean income of $30,000 and a standard deviation of $3,000.

580.1) (i) 250 students earned more than $30,000.

(ii) 341 students earned between $27,000 and $33,000. (iii) 239 students earned between $24,000 and $30,000. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

580.2) (i) 250 students earned more than $30,000.

(ii) 341 students earned between $27,000 and $33,000. (iii) 290 students earned between $24,000 and $30,000. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

580.3) (i) 250 students earned more than $30,000.

(ii) 314 students earned between $27,000 and $33,000. (iii) 239 students earned between $24,000 and $30,000. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

580.4) (i) 250 students earned more than $30,000.

(ii) 500 students earned between $20,000 and $40,000. (iii) 3 students earned less than $22,500. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

580.5) (i) 250 students earned more than $30,000.

(ii) 500 students earned between $20,000 and $40,000. (iii) 6 students earned less than $22,500. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

580.6) (i) 250 students earned more than $30,000.

(ii) 500 students earned between $20,000 and $40,000. (iii) 11 students earned more than $36,000. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

581)

A loaf of bread is normally distributed with a mean of 22 ounces and a standard deviation of ½ ounce.

581.1) (i) The probability that a loaf of bread is < 20 ounces is 0.0.

(ii) The probability that a loaf of bread is > 21 ounces is 0.9772. (iii) The probability that a loaf of bread is < 24 ounces is 1.0. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

581.2) (i) The probability that a loaf of bread is < 20 ounces is 0.0.

(ii) The probability that a loaf of bread is > 21 ounces is 0.9772. (iii) The probability that a loaf of bread is < 24 ounces is 0.00. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

581.3) (i) The probability that a loaf of bread is > 23 ounces is 0.0228.

581.4) (i) The probability that a loaf of bread is < 20 ounces is 0.0.

(ii) The probability that a loaf of bread is > 21 ounces is 0.4772. (iii) The probability that a loaf of bread is < 24 ounces is 1.0. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

581.5) (i) The probability that a loaf of bread is between 20.75 and 23.25 ounces is 0.9876.

(ii) The probability that a loaf of bread is > 21 ounces is 0.9772. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (i) are false statements.

581.6) (i) The probability that a loaf of bread is 22.25 ounces is 0.0.

(ii) The probability that a loaf of bread is > 21 ounces is 0.9772. (iii) The probability that a loaf of bread is < 24 ounces is 1.0. A) (i), (ii), and (iii) are all correct statements B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

581.7) (i) The probability that a loaf of bread is 22.25 ounces is 0.0.

(ii) The probability that a loaf of bread is between 21.75 and 22.25 ounces is 0.3830. (iii) The probability that a loaf of bread is < 24 ounces is 1.0. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

581.8) (i) The probability that a loaf of bread is between 20.75 and 23.25 ounces is 0.7662.

582)

Two business major students in two different sections of economics were comparing test scores. The following gives the students' scores, class mean and standard deviation for each section. Section

Score

582.1) (i) The student from Section 2 scored better compared to the rest of their section.

(ii) The z-score of the student from section 1 is 1.28. (iii) The z-score of the student from section 2 is 1.87. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

582.2) (i) The student from Section 2 scored better compared to the rest of their section.

(ii) The z-score of the student from section 1 is 1.82. (iii) The z-score of the student from section 2 is 1.87. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

582.3) (i) The student from Section 2 scored better compared to the rest of their section.

(ii) The z-score of the student from section 1 is 1.28. (iii) The z-score of the student from section 2 is 2.87. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

583)

One classic use of the normal distribution is inspired by a letter to Dear Abbey in which a wife claimed to have given birth 308 days after a brief visit from her husband who was serving in the Navy. The lengths of pregnancies are normally distributed with a mean of 268 days and a standard deviation of 15 days. Given this information.

583.1) (i) the probability of a pregnancy lasting 308 days or longer is 0.0038.

(ii) The result suggests that the husband is not the father of the child. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (i) are false statements.

583.2) (i) the probability of a pregnancy lasting 300 days or longer is 0.0166.

583.3) (i) the probability of a pregnancy lasting 308 days or longer is 0.0038.

(ii) The result suggests that the husband is the father of the child. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are false statements.

583.4) (i) the probability of a pregnancy lasting 300 days or longer is 0.0166.

584)

Assume that human body temperatures are normally distributed with a mean of 36.4°C and a standard deviation of 0.7°C. If we define a fever to be a body temperature above 38.0°C. (i) 01.1% of normal and healthy persons would be considered to have a fever. (ii) This suggests that a cut-off of 38.0°C is appropriate. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are false statements.

585)

Replacement times for TV sets are normally distributed with a mean of 8.2 years and a standard deviation of 1.1 years, (based on data from "Getting Things Fixed, " Consumer Reports).

585.1) (i) The replacement time that separated the top 20% from the bottom 80% is 9.124 years.

(ii) The probability that a randomly selected TV will be replaced in less than 4.0 years is 0.00. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are false statements.

585.2) (i) The replacement time that separated the top 20% from the bottom 80% is 9.124 years.

(ii) The probability that a randomly selected TV will be replaced in less than 4.0 years is 0.40. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are false statements.

585.3) (i) The replacement time that separated the top 20% from the bottom 80% is 9.124 years.

(ii) The probability that a randomly selected TV will be replaced after more than 10.0 years is 0.0505. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are false statements.

585.4) (i) If you want to provide a warranty so that only 3% of the TV sets will be replaced

before the warranty expires, the length of warranty you would recommend would be 6.13 years. (ii) The probability that a randomly selected TV will be replaced after more than 10.0 years is 0.0505. A) (i) and (ii) are correct statements. B) (i) is a correct statement but not (ii). C) (ii) is a correct statement but not (i). D) (i) and (ii) are false statements.

586)

Normally distributed observations such as a person's weight, height, or shoe size occur quite frequently in nature. Business people who are aware of this use it to their advantage. A purchasing agent for a large retailer buying 15,000 pairs of women's shoes used the normal curve to decide on the order quantities for the various sizes. If women's average shoe size is 7.5 with a standard deviation of 1.5, how many pairs should be ordered between sizes 6.5 and 9? A) 8640 B) 8849 C) 8664 D) 8864 E) 8940

587)

Normally distributed observations such as a person's weight, height or shoe size occur quite frequently in nature. Business people who are aware of this use it to their advantage. A purchasing agent for a college bookstore buying 300 golf shirts used the normal curve to decide on the order quantities for the various sizes. If men's average shirt size is 15.5 with a standard deviation of.50, how many shirts should be ordered in sizes over 16.5? A) 7 B) 8 C) 9 D) 10 E) 6

During the 4th wave of the pandemic in Canada, the number of daily new cases was normally distributed around a mean of 3,000 and a standard deviation of 400.

588)

588.1) Using the empirical rule, what is the probability that there will be between 2,600 and

3,400 cases reported tomorrow? A) 0% B) 68% C) 95.5% D) 99.7% E) 100%

588.2) Using the empirical rule, what is the probability that there will be between 2,200 and

3,800 cases reported tomorrow? A) 0% B) 68% C) 95.5% D) 99.7% E) 100%

588.3) Using the empirical rule, what is the probability that there will be between 1,800 and

4,200 cases reported tomorrow? A) 0% B) 68% C) 95.5% D) 99.7% E) 100%

588.4) Using the empirical rule, what is the probability that there will be over 3,400 tomorrow? A) 50% B) 16% C) 2.25% D) 0.15% E) 0%

588.5) Using the empirical rule, what is the probability that there will be over 3,800 tomorrow? A) 50% B) 16% C) 2.25% D) 0.15% E) 0%

588.6) Using the empirical rule, what is the probability that there will be over 4,200 tomorrow? A) 50% B) 16% C) 2.25% D) 0.15% E) 0%

588.7) Using the empirical rule, what is the probability that there will be less than 3,000

tomorrow? A) 50% B) 16% C) 2.25% D) 0.15% E) 0%

588.8) Using the Z-table, what is the probability that there will be over 3,400 tomorrow? A) 50% B) 15.87% C) 84.13% D) 16% E) 100%

588.9) Using the empirical rule, what is the probability that there will be over 1,800 tomorrow? A) 50% B) 84% C) 97.75% D) 99.85% E) 100%

588.10) Using the empirical rule, what is the probability that there will be over 2,200 tomorrow? A) 50% B) 84% C) 97.75% D) 99.85% E) 100%

588.11) Using the empirical rule, what is the probability that there will be over 2,600 tomorrow? A) 50% B) 84% C) 97.75% D) 99.85% E) 100%

588.12) Using the Z table, what is the probability that there will be over 2,000 tomorrow? A) 50% B) 84% C) 99.38% D) 99.85% E) 100%

588.13) Using the empirical rule, what is the there will be less than 1,800 tomorrow? A) 0% B) 0.15% C) 2.25% D) 16% E) 50%

588.14) Using the empirical rule, what is the probability that there will be less than 2,200

tomorrow? A) 0% B) 0.15% C) 2.25% D) 16% E) 50%

588.15) Using the empirical rule, what is the probability that there will be less than 2,600

tomorrow? A) 0% B) 0.15% C) 2.25% D) 16% E) 50%

588.16) Using the Z table, symmetrically distributed, the middle 95% of cases will be between

which 2 amounts? A) 2013 to 3690 cases B) 2200 to 3800 cases C) 1454 to 4545 cases D) 2216 to 3784 cases E) 2231 to 3769

Answer Key Test name: chapter 6 485) D 486) C 487) A 488) A 489) B 490) A 491) B 492) C 493) B 494) C 495) B 496) C 497) Section Break 497.1) D 497.2) A 497.3) B 498) Section Break 498.1) D 498.2) B 499) D 500) B 501) A 502) C 503) A 504) A 505) D 506) A 507) A 508) B 509) D 510) C 511) D 512) A 513) B 514) A 515) D 516) D

517) C 518) Section Break 518.1) D 518.2) B 518.3) B 519) B 520) A 521) D 522) E 523) C 524) C 525) D 526) D 527) D 528) D 529) C 530) B 531) B 532) D 533) A 534) B 535) B 536) Section Break 536.1) B 536.2) C 536.3) A 536.4) A 536.5) D 536.6) C 537) B 538) A 539) A 540) D 541) D 542) C 543) D 544) A 545) C 546) A 547) A

548) Section Break 548.1) B 548.2) E 548.3) C 549) D 550) C 551) A 552) D 553) B 554) D 555) D 556) A 557) Section Break 557.1) C 557.2) A 557.3) B 558) Section Break 558.1) C 558.2) B 558.3) A 559) C 560) B 561) D 562) A 563) C 564) Section Break 564.1) C 564.2) C 564.3) D 564.4) C 565) B 566) B 567) C 568) A 569) A 570) E 571) E 572) A 573) D 574) D

575) A 576) E 577) E 578) A 579) B 580) C 581) B 582) Section Break 582.1) A 582.2) D 582.3) C 582.4) A 582.5) D 582.6) A 583) Section Break 583.1) A 583.2) D 583.3) A 583.4) C 583.5) A 583.6) A 583.7) A 583.8) C 584) Section Break 584.1) A 584.2) C 584.3) D 585) Section Break 585.1) A 585.2) A 585.3) B 585.4) B 586) A 587) Section Break 587.1) A 587.2) B 587.3) A 587.4) A 588) B 589) A

590) Section Break 590.1) B 590.2) C 590.3) D 590.4) B 590.5) C 590.6) D 590.7) A 590.8) B 590.9) D 590.10) C 590.11) B 590.12) C 590.13) B 590.14) C 590.15) D 590.16) D

Student name:__________ 589)

590)

As the sample size increase, the value of the standard error of the proportion decreases. ⊚ true ⊚ false

i. It is often not feasible to study the entire population because it is impossible to check all the items in the population. ii. Sampling a population is often necessary because the cost of studying all the items in the population is prohibitive. iii. Sampling is a sign of laziness on the part of the statistician. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

591)

i. A simple random sample assumes that each item or person in the population has an equal chance of being included. ii. We can expect some difference between sample statistics and the corresponding population parameters. This difference is called the sampling error. iii. A sampling distribution of the means is a probability distribution consisting of a list of all possible sample means of a given sample size selected from a population and the probability of occurrence associated with each sample mean. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

592)

i. If probability sampling is done, each item in the population has a chance of being chosen. ii. If the size of a sample equals the size of the population, we would not expect any error in estimating the population parameter. A) (i) and (ii) are both correct statements. B) (i) is correct but not (ii). C) (ii) is correct but not (i). D) (i) and (ii) are both false statements.

593)

i. If the sample size keeps getting larger and larger and finally equals the size of the population, there would be no error in predicting the population mean because the sample size and the size of the population would be the same. ii. A simple random sample assumes that each item or person in the population has an equal chance of being included. iii. We can expect some difference between sample statistics and the corresponding population parameters. This difference is called the sampling error. A) (i), (ii), and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

594)

What is it called when all the items in a population have a chance of being selected in a sample? A) Random sampling B) z-score C) Sampling error D) Non probability sampling

595)

Manufacturers were subdivided into groups by volume of sales. Those with more than $100 million in sales were classified as Class A large; those from $50 to $100 million as Class A medium size; and those between $25 and $50 million, and so on. Samples were then selected from each of these groups. What is this type of sampling called? A) Simple random B) Stratified random C) Cluster D) Systematic

596)

Suppose we select every fifth invoice in a file. What type of sampling is this? A) Simple random B) Stratified random C) Cluster D) Systematic

597)

We wish to study the advertising expenditures for the 200 largest companies in Canada. Suppose the objective of the study is to determine whether firms with high returns on equity (a measure of profitability) spent more of each sales dollar on advertising than firms with a low return or deficit. To make sure that the sample is a fair representation of the 200 companies, the companies are grouped on percent return on equity Stratum

Profitability (return on equity)

30% and over

0.02

20 up to 30%

0.10

10 up to 20%

108

0.54

0 up to 10%

0.33

Deficit

0.01

200

1.00

Total

Number of Firms

Relative Frequency

Number Sampled

What is this type of sampling called? A) Simple random B) Stratified random C) Cluster D) Systematic

598)

What is the difference between a sample mean and the population mean called? A) Standard error of the mean B) Sampling error C) Interval estimate D) Point estimate

599)

Suppose we select every tenth invoice in a file. What type of sampling is this? A) Random B) Cluster C) Stratified D) Systematic

600)

A province-wide sample survey is to be made. First, the province is subdivided into counties. Seven counties are selected at random and further sampling is concentrated on these seven counties. What type of sampling is this? A) Simple random B) Non proportional C) Cluster D) Stratified

601)

602)

Sampling error is the difference between a corresponding sample statistic and the A) sample mean. B) biased sample. C) population parameter. D) chance error.

i. An estimate of the population mean based on a large sample is less reliable than an estimate made using a small sample. ii. The standard error of the mean will vary according to the size of the sample that is in the denominator. As the sample size n gets larger, the variability of the sample means gets smaller. iii. To determine the value of the standard error of the mean, the total error is divided by the sample size. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement, but not (ii) or (iii). C) (ii) is a correct statement, but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

603)

(i) As the sample size ( n) increases, the spread in the distribution of the sample means stays the same. (ii) If the sampling size equals the population size, the sampling error is 1. (iii) If a population is normally distributed, the sampling distribution of the mean is normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement, but not (i) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

604)

Which of the following is the standard error of the mean? A) µ B) x/n C) D) s/√n

605)

All possible samples of size n are selected from a population and the mean of each sample is determined. What is the mean of the sample means? A) Exactly the same as the population mean B) Larger than the population mean C) Smaller than the population mean D) Cannot be estimated in advance

606)

The mean of all possible sample means is equal to the: A) population variance. B) ς2/ n. C) sample variance. D) population mean.

607)

An experiment involves randomly selecting a sample of 256 middle managers for study. One item of interest is their mean annual income. The sample mean is computed to be $35,420 and the sample standard deviation is $2,050. What is the standard error of the mean? A) $5.65 B) $128.13 C) $138.36 D) $2,050 E) $8.01

608)

A group of statistics students decided to conduct a survey at their university to find the average (mean) amount of time students spend studying per week. Based on a simple random sample, they surveyed 144 students. The statistics showed that students studied an average of 20 hours per week with a standard deviation of 10 hours. What is the standard error of the mean? A) 0.83 B) 10 C) 0.5 D) 2

609)

As the size of the sample increases, what happens to the shape of the sampling means? A) Cannot be predicted in advance B) Approaches a normal distribution C) Positively skewed D) Negatively skewed

610)

What sample statistic is used to estimate a population parameter? A) Parameter B) Sampling error C) D) Interval estimate

611)

For a population that is not normally distributed, the distribution of the sample means will: A) be negatively skewed. B) approach the normal distribution. C) be positively skewed. D) take the same shape as the population.

612)

i. If a population is not normally distributed, the sampling distribution of the sample means tends to approximate a normal distribution. ii. The Central Limit Theorem states that if the sample size n is sufficiently large, the sampling distribution of the means will be approximately normal no matter whether the population is normally distributed, skewed, or uniform. iii. Based on the sampling distribution of the means and the central limit theorem, the sample mean can be used as a good estimator of the population mean, assuming that the size of the sample is sufficiently large. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement, but not (ii) or (iii). C) (ii) is a correct statement, but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

613)

An accounting firm is planning for the next tax preparation season. From last year's returns, the firm collects a systematic random sample of 100 filings. The 100 filings showed an average preparation time of 90 minutes with a standard deviation of 140 minutes.

613.1) What is the standard error of the mean? A) 14 minutes B) 140 minutes C) 1.4 minutes D) 90 minutes

613.2) What assumptions do you need to make about the shape of the population distribution of

all possible tax preparation times to make inferences about the average time to complete a tax form? A) The population distribution is skewed to the right. B) The population distribution is skewed to the left. C) The population distribution is normal. D) The shape of the population distribution does not matter.

613.3) What is the probability that the mean completion time will be more than 120 minutes? A) Approximately zero B) 0.0832 C) 0.4168 D) 0.0162

613.4) What is the probability that the mean completion time is between 1 and 2 hours, i.e., 60

and 120 minutes? A) Approximately 0 B) 0.1664 C) 0.8336 D) 0.967

613.5) What is the probability that a sample mean would exceed 90 minutes per filing? A) 1.0 B) 0.5 C) 1.96 D) Cannot be calculated based on the given information.

613.6) What is the probability of finding a sample mean less than 80 minutes? A) 0.7143 B) 0.7625 C) 0.2375 D) 0.0180

613.7) What is the probability that average preparation time is between 80 and 90 minutes? A) 0.7143 B) 0.7625 C) 0.2375 D) 0.2625

614)

Prince Edward Island Fisheries and Environment has been feeding a special food to rainbow trout fingerlings in a pond. A sample of the weights of 40 trout revealed that the mean weight is 402.7 grams and the population standard deviation 8.8 grams. What is the probability that the mean weight for a sample of 40 trout exceeds 405.5 grams? A) 0.3783 B) 0.0221 C) 1.0 D) 0.5

615)

Suppose a research firm conducted a survey to determine the average amount of money steady smokers spend on cigarettes during a week. A sample of 100 steady smokers revealed that the sample mean is $20 and the population standard deviation is $5. What is the probability that a sample of 100 steady smokers spend between $19 and $21? A) 0.4772 B) 0.0228 C) 0.9545 D) 0.3759

616)

An experiment involves selecting a random sample of 256 middle managers at random for study. One item of interest is their mean annual income. The sample mean is computed to be $35,420 and the sample standard deviation is $2,050. What is the standard error of the mean? A) $128.13 B) $138.36 C) $2,050 D) $8.01

617)

The mean weight of trucks traveling on a particular section of Highway 475 is not known. A provincial highway inspector needs an estimate of the mean. He selects a random sample of 49 trucks passing the weighing station and finds the mean is 15.8 tonnes, assuming a population standard deviation of 4.2 tonnes. What is probability that a truck will weigh less than 14.3 tonnes? A) 0.0062 B) 0.3632 C) 0.1368 D) 0.4938

618)

Suppose a research firm conducted a survey to determine the average amount of money steady smokers spend on cigarettes during a week. A sample of 100 steady smokers revealed that the sample mean is $80 and assuming the population standard deviation is $20. What is the probability that a sample of 100 steady smokers spend between $76 and $84? A) 0.4772 B) 0.0228 C) 0.9544 D) 0.3400 E) 0.9999

619)

Mileage tests were conducted on a randomly selected sample of 100 newly developed automobile tires. The average tread wear was found to be 100,000 kilometres with a standard deviation of 7,000 kilometres. What is the best estimate of the average tread life in kilometres for the entire population of these tires? A) 100,000 B) 7,000 C) (100,000/100) D) (7000 )

620)

The Intelligence Quotient (IQ) test scores are normally distributed with a mean of 100 and a standard deviation of 15. i. What is the probability that a person would score between 85 and 115? ii. Given a class with 25 students, what is the probability that the class average IQ score is between 85 and 115? A) 0.3414, 0.0228 B) 0.6826, 0.9772 C) 0.6826, Approximately 1.0 D) 1.0, 0.9544

621)

The Intelligence Quotient (IQ) test scores are normally distributed with a mean of 100 and a standard deviation of 15. i. What is the probability that a person would score 130 or more on the test? ii. You enrolled in a class of 25 students. What is the probability that the class' average IQ exceeds 130? A) 0.0228, 0.4987 B) 0.4772, 0.300 C) 0.4772, 0.0026 D) 0.0228, approximately zero

622)

The daily sales of a small retail store in Toronto for the last 365 days are normally distributed with a mean of $2,050, and a standard deviation of $300. i. What is the probability of daily sales exceeding $2,500? ii. From a sample of 49 days, what is the probability of having a sample mean less than $2,500? A) 0.4332, 0.0668 B) 0.0668, 0.9332 C) 0.4332, approximately 100% D) 0.0668, Approximately 0% E) 0.0668, Approximately 100%

623)

The daily sales of a small retail store in Toronto for the last 365 days are normally distributed with a mean of $2,050, and a standard deviation of $300. From a sample of 49 days, what is the probability of having a sample mean more than $2,000? A) 0.3790 B) 0.8790 C) 0.121 D) Approximately zero E) Approximately 100%

624)

A new extended-life light bulb has an average service life of 750 hours, with a standard deviation of 50 hours. The shape of this distribution is unknown. From a sample of 100 light bulbs, about what percent of the bulbs will last more than 700 hours? A) 100% B) 34.13% C) 84.13% D) 50%

625)

A study of a company's practice regarding the payment of invoices revealed that on the average an invoice was paid 20 days after it was received. The population standard deviation equaled five days. A sample of 25 invoices is selected. Assuming that the distribution is normal, what percent of the sampled invoices were paid within 15 days of receipt? A) 100% B) 37.91% C) 34.13% D) 86.74%

626)

The mean rent for a one-bedroom apartment in the Greater Toronto Area is $2,000 per month. The distribution of the monthly costs does not follow the normal distribution. In fact, it is positively skewed.

626.1) What is the probability of selecting a sample of 36 one-bedroom apartments and finding

the mean to be at least $1,500 per month? Assume the standard deviation of the sample is $300. A) 34.13% B) 84.13% C) 50% D) 100%

626.2) What is the probability of selecting a sample of 36 one-bedroom apartments and finding

the mean to be under $1,500 per month? The standard deviation of the population is $300. A) 34.13% B) 84.13% C) 0% D) 100%

626.3) What is the probability of selecting a sample of 36 one-bedroom apartments and finding

the mean to be under $1,800 per month? The standard deviation of the population is $300. A) 34.13% B) 0% C) 50% D) 100%

627)

GreenFacts, a non-profit organization, reports that the average adult in Europe consumed 17 litres of alcohol last year. The population standard deviation is 2.1 litres. If we randomly select 42 European adults, what is the probability that the sample mean is more than 17.8 litres? A) 0.0068 B) 0.4873 C) 0.0058 D) 0.4863 E) 0.0680

628)

It has been estimated that 25% of all university students switch majors within their first two years of starting classes. If a random sample of 500 third-year students is taken at a city university, what is an estimate of the probability that 20% or more had switched majors within their first two years? A) 0.4951 B) 0.0049 C) 0.9951 D) 0.5059

629)

Dawson's Repair Service orders parts from an electronic company who advertises its parts to be no more than 2% defective.

629.1) What is the probability that Bill Dawson finds 4 or more parts out of a sample of 50 to be

defective? A) Almost 100% B) 0.0012 C) About 1% D) Almost 50%

629.2) What is the probability that Bill Dawson finds 2 or more parts out of a sample of 50 to be

defective? A) Almost 100% B) 0.0217 C) 0.1562 D) Almost 50% E) 0.4783

629.3) What is the probability that Bill Dawson finds 3 or more parts out of a sample of 50 to be

defective? A) Almost 100% B) 2.17% C) 15.62% D) Almost 50% E) 34.38%

629.4) What is the probability that Bill Dawson finds 3 or more parts out of a sample of 60 to be

defective? A) 4.85% B) 1.34% C) 15.62% D) Almost 50% E) 22.96%

629.5) What is the probability that Bill Dawson finds 4 or more parts out of a sample of 60 to be

defective? A) 4.85% B) 0.47% C) 15.62% D) Almost 50% E) 22.96%

629.6) What is the probability that Bill Dawson finds 2 or more parts out of a sample of 60 to be

defective? A) 4.85% B) 0.49% C) 15.62% D) Almost 50% E) 23.96%

630)

A convenience store estimates that 25% of its customers come in to buy milk. What is the probability that out of the next 200 customers, 60 or fewer will buy milk? A) 0.4488 B) 0.9488 C) 0.0512 D) Almost no chance E) 0.0505

631)

A retailer claims that 90% of its customers are "pleased" or "very pleased" with the customer service. In a survey of 300 customers taken last week, what is the probability that 84% or more will be "pleased" or "very pleased" with the service? A) 0.1736 B) 0.5736 C) 0.3464 D) Almost 100% E) Almost no chance

632)

A retailer claims that 90% of its customers are "pleased" or "very pleased" with the customer service. In a survey of 300 customers taken last week, what is the probability that between 80% and 90% will be "pleased" or "very pleased" with the service? A) 0.1736 B) 0.5736 C) 0.3464 D) Almost 100% E) Almost 50%

633)

70% of North American women have pierced ears. In a survey of 49 women, what is the probability that less than 30 had pierced ears? A) 0.0901 B) 0.5901 C) 0.9099 D) 0.4099

634)

70% of North American women have pierced ears. For a survey of 49 women, what is the standard error? A) 0.5 B) 0.7 C) 0.0655 D) 0.4245 E) 0.3

635)

Alpha Corporation receives a shipment of flour every morning from their supplier. The flour is in 40 kg bags and Alpha will reject any shipment that is more than 5% underweight.

635.1) The foreman samples 50 bags with each shipment and if the bags average more than 5%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.03082 B) 0.0095 C) 0.00707 D) 0.00095 E) 0.09747

635.2) The foreman samples 60 bags with each shipment and if the bags average more than 4%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.0250 B) 0.0253 C) 0.00064 D) 0.0064 E) 0.08

635.3) The foreman samples 35 bags with each shipment and if the bags average more than 5%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.0368 B) 0.00095 C) 0.0014 D) 0.0471 E) 0.00386

635.4) The foreman samples 60 bags with each shipment and if the bags average more than 5%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.02814 B) 0.01504 C) 0.00792 D) 0.08898 E) 0.1234

635.5) The foreman samples 36 bags with each shipment and if the bags average more than 5%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.00132 B) 0.0363 C) 0.00792 D) 0.08898 E) 0.1234

635.6) Alpha Corporation receives a shipment of flour every morning from their supplier. The

flour is in 40 kg bags and Alpha will reject any shipment that is more than 4% underweight. The foreman samples 60 bags with each shipment and if the bags average more than 4% underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.00132 B) 0.0253 C) 0.00064 D) 0.08898 E) 0.0250

635.7) The foreman samples 50 bags with each shipment and if the bags average more than 4%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.00132 B) 0.000768 C) 0.00064 D) 0.02771 E) 0.0250

635.8) The foreman samples 40 bags with each shipment and if the bags average more than 4%

underweight, the whole shipment is returned to the supplier. Determine the value for the standard error of the proportion. A) 0.03098 B) 0.00096 C) 0.00064 D) 0.02771 E) 0.0250

636)

(i) The type of sampling when a population is first divided into subgroups and then a sample is selected from each subgroup is called stratified random sampling. (ii) Auditors may select every 20th file starting with say, the 5th file in the top drawer. Then file numbers 25, 45, 65, 85, are audited. This type of sampling is called systematic sampling. (iii) The mean of a population is called a parameter. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

637)

(i) The type of sampling when a population is first divided into subgroups and then a sample is selected from each subgroup is called random sampling. (ii) Auditors may select every 20th file starting with say, the 5th file in the top drawer. Then file numbers 25, 45, 65, 85, are audited. This type of sampling is called systematic sampling. (iii) The mean of a population is called a parameter. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

638)

(i) The type of sampling when a population is first divided into subgroups and then a sample is selected from each subgroup is called stratified random sampling. (ii) Auditors may select every 20th file starting with say, the 5th file in the top drawer. Then file numbers 25, 45, 65, 85, are audited. This type of sampling is called cluster sampling. (iii) The mean of a population is called a parameter. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

639)

(i) For populations scattered in a wide area, the preferred technique for sampling is cluster sampling. (ii) If the population can be divided into homogeneous subgroups, stratified random sampling is the best sampling method to use. (iii) If every k-th item in the population sequence is selected, you are using systematic random sampling. A) (i), (ii), and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

640)

(i) For populations scattered in a wide area, the preferred technique for sampling is simple random sampling. (ii) If the population can be divided into homogeneous subgroups, stratified random sampling is the best sampling method to use. (iii) If every k-th item in the population sequence is selected, you are using systematic random sampling. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

641)

(i) For populations scattered in a wide area, the preferred technique for sampling is cluster sampling. (ii) If the population can be divided into homogeneous subgroups, stratified random sampling is the best sampling method to use. (iii) If every k-th item in the population sequence is selected, you are using cluster sampling. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

642)

(i) The standard error of the mean is the standard deviation of the sampling distribution of the sample means. (ii) The standard deviation of the sampling distribution of the mean is always smaller than the standard deviation of the population under study unless n=1 and then they're equal. (iii) For a sampling distribution of the means, 95% of the means would be between ± 1.96 standard deviations. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

643)

(i) The standard error of the mean is the standard deviation of the sampling distribution of the sample means. (ii) The standard deviation of the sampling distribution of the mean is always larger than the standard deviation of the population under study unless n=1 and then they're equal. (iii) For a sampling distribution of the means, 95% of the means would be between ± 1.96 standard deviations. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

644)

(i) The standard error of the mean is the standard deviation of the sampling distribution of the sample means. (ii) The standard deviation of the sampling distribution of the mean is always smaller than the standard deviation of the population under study unless n=1 and then they're equal. (iii) For a sampling distribution of the means, 90% of the means would be between ± 1.96 standard deviations. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

645)

(i) As the sample size ( n) increases, the spread in the distribution of the sample means decreases. (ii) If the sampling size equals the population size, the sampling error is zero. (iii) If a population is normally distributed, the sampling distribution of the mean is normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

646)

(i) As the sample size ( n) increases, the spread in the distribution of the sample means increases. (ii) If the sample size equals the population size, the sample error is zero. (iii) If a population is normally distributed, the sampling distribution of the mean is normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

647)

(i) As the sample size ( n) increases, the spread in the distribution of the sample means decreases. (ii) If the sampling size equals the population size, the sampling error is 1. (iii) If a population is normally distributed, the sampling distribution of the mean is normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

648)

During the fourth wave of the pandemic 83% of all Canadians were fully vaccinated.

648.1) If a sample of 30 students were surveyed over Zoom, determine the value of the standard

error of proportion. A) 0 B) 0.0119 C) 0.0376 D) 0.0686 E) 1.0

648.2) If a sample of 100 students were surveyed over Zoom, determine the value of the

standard error of proportion. A) 0 B) 0.0119 C) 0.0376 D) 0.0686 E) 1.0

648.3) If a sample of 1000 students were surveyed over Zoom, determine the value of the

standard error of proportion. A) 0 B) 0.0119 C) 0.0376 D) 0.0686 E) 1.0

648.4) If a sample of 30 students were surveyed over Zoom, what is the probability that less than

27 were vaccinated? A) 0 B) 0.2266 C) 0.8463 D) 0.9688 E) 1.0

648.5) If a sample of 100 students were surveyed over Zoom, what is the probability that less

than 90 were vaccinated? A) 0 B) 0.0314 C) 0.8463 D) 0.9688 E) 1.0

648.6) If a sample of 1000 students were surveyed over Zoom, what is the probability that less

than 900 were vaccinated? A) 0 B) 0.7734 C) 0.8463 D) 0.9688 E) 1.0

649)

During the fourth wave of the pandemic the mean daily number of COVID-19 patients in a hospital was 88 with a standard deviation of 25.

649.1) From a sample of 30 days determine the standard error. A) 0 B) 1.77 C) 2.5 D) 4.564

649.2) From a sample of 100 days determine the standard error. A) 0 B) 1.77 C) 2.5 D) 4.564

649.3) From a sample of 200 days determine the standard error. A) 0 B) 1.77 C) 2.5 D) 4.564

649.4) From a sample of 30 days, what is the probability that the sample mean will be over 95

patients? A) 0 B) 0.0026 C) 0.0626 D) 1.0

649.5) From a sample of 100 days, what is the probability that the sample mean will be over 95

patients? A) 0 B) 0.0026 C) 0.0626 D) 1.0

649.6) From a sample of 200 days, what is the probability that the sample mean will be over 95

patients? A) 0 B) 0.0026 C) 0.0626 D) 1.0

650)

During the fourth wave of the pandemic 20% of the patients admitted would enter the ICU.

650.1) From a sample of 100 patients admitted, what is the probability between 19% and 21%

were admitted to the ICU? A) 0.1974 B) 0.7887 C) 0.9876 D) 0.9999

650.2) From a sample of 100 patients admitted, what is the probability between 15% and 25%

were admitted to the ICU? A) 0.1974 B) 0.7887 C) 0.9876 D) 0.9999

650.3) From a sample of 100 patients admitted, what is the probability between 10% and 30%

were admitted to the ICU? A) 0.1974 B) 0.7887 C) 0.9876 D) 0.9999

650.4) From a sample of 100 patients admitted, what is the probability over 15% would be

admitted to the ICU? A) 0.1974 B) 0.7887 C) 0.8944 D) 0.9999

Answer Key Test name: chapter 7 1) TRUE 2) B 3) A 4) A 5) A 6) A 7) B 8) D 9) B 10) B 11) D 12) C 13) C 14) C 15) B 16) D 17) A 18) D 19) B 20) A 21) B 22) C 23) B 24) A 25) Section Break 25.1) A 25.2) C 25.3) D 25.4) D 25.5) B 25.6) C 25.7) D 26) B 27) C 28) A 29) A 30) C

31) A 32) C 33) D 34) E 35) B 36) A 37) A 38) Section Break 38.1) D 38.2) C 38.3) B 39) A 40) C 41) Section Break 41.1) B 41.2) C 41.3) B 41.4) A 41.5) B 41.6) E 42) B 43) D 44) E 45) A 46) C 47) Section Break 47.1) A 47.2) B 47.3) A 47.4) A 47.5) B 47.6) B 47.7) D 47.8) A 48) A 49) D 50) C 51) A 52) D 53) B

54) A 55) C 56) B 57) A 58) D 59) C 60) Section Break 60.1) D 60.2) C 60.3) B 60.4) C 60.5) D 60.6) E 61) Section Break 61.1) D 61.2) C 61.3) B 61.4) C 61.5) B 61.6) A 62) Section Break 62.1) A 62.2) B 62.3) C 62.4) C

Student name:__________ 651)

i. The 95 percent confidence interval states that 95 percent of the sample means of a specified sample size selected from a population will lie within plus and minus 1.96 standard deviations of the hypothesized population mean. ii. A distribution of sample means is normally distributed with a mean equal to the population mean and a standard deviation equal to the standard error of the mean. iii. A sample mean is the best point estimate of a population mean. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

652)

Which of the following would be used as a point estimate for the population mean ( µ)? A) σ B) x/n C) D) s E) p

653)

Mileage tests were conducted on a randomly selected sample of 100 newly developed automobile tires. The average tread life was found to be 80,000 kilometres with a standard deviation of 5,600 kilometres. What is the best estimate of the average tread life in kilometres for the entire population of these tires? A) 80,000 B) 5,600 C) (80,000/100) D) (5,600/100)

654)

A sample mean is the best point estimate of the A) population standard deviation. B) population median. C) population mean. D) the sample standard deviation. E) the population variance.

655)

A sample standard deviation is the best point estimate of the A) population range. B) population skewness. C) population mode. D) population standard deviation. E) population variance.

656)

Recently, a university surveyed recent graduates of the English Department for their starting salaries. One hundred graduates returned the survey. The average salary was $35,000 with a standard deviation of $2,000. What is the best point estimate of the population mean? A) $25,000 B) $2,000 C) $500 D) $400 E) $35,000

657)

A confidence interval for a population mean: A) estimates the population range. B) estimates a likely interval for a population mean. C) estimates a likelihood or probability. D) estimates the population standard deviation.

658)

A 95% confidence interval infers that the population mean is: A) between 0 and 100%. B) within ± 1.96 standard deviations of the sample mean. C) within ± 1.96 standard errors of the sample mean. D) within ± 1.645 standard deviations of the sample mean. E) too large.

659)

When a confidence interval for a population mean is constructed from sample data, A) we can conclude that the population mean is in the interval. B) we can conclude that the population mean is not in the interval. C) we can conclude, with a stated level of confidence, that the population mean is in the interval. D) we cannot make any inferences.

660)

Dottie Kleman is the "Cookie Lady." She bakes and sells cookies at 50 different locations. Ms. Kleman is concerned about absenteeism among her workers. The information below reports the number of days absent for a sample of 10 workers during the last two-week pay period. 4

The sample mean is calculated to be 1.8 and sample standard deviation is 1.1353. Develop a 95% confidence interval for the population mean. Assume that the population distribution is normal.

660.1) Is it reasonable to conclude that the typical worker does not miss any days during a pay

period? A) [0.99, 2.61] It is unreasonable to conclude that the mean number of days of work

missed is 0 per employee. B) [0.99, 2.61] It is reasonable to conclude that the mean number of days of work missed is 0 per employee. C) [-0.99, -2.61] It is unreasonable to conclude that the mean number of days of work missed is 0 per employee. D) [-0.99, -2.61] It is reasonable to conclude that the mean number of days of work missed is 0 per employee.

660.2) Is it reasonable to conclude that the typical worker misses 1 day during a pay period? A) [0.99, 2.61] It is unreasonable to conclude that the mean number of days of work

missed is1per employee. B) [0.99, 2.61] It is reasonable to conclude that the mean number of days of work missed is 1 per employee. C) [-0.99, -2.61] It is unreasonable to conclude that the mean number of days of work missed is 1 per employee. D) [-0.99, -2.61] It is reasonable to conclude that the mean number of days of work missed is 1 per employee.

660.3) Is it reasonable to conclude that the typical worker misses 2 days during a pay period? A) [0.99, 2.61] It is unreasonable to conclude that the mean number of days of work

missed is 2 per employee. B) [0.99, 2.61] It is reasonable to conclude that the mean number of days of work missed is 2 per employee. C) [1.99, 2.61] It is unreasonable to conclude that the mean number of days of work missed is 2 per employee. D) [0.99, 1.61] It is reasonable to conclude that the mean number of days of work missed is 2 per employee.

661)

Recently, a university surveyed recent graduates of the English Department for their starting salaries. Four hundred graduates returned the survey. The average salary was $25,000. The population standard deviation is known to be $2,500. Interpret the results of the 95% confidence interval. A) The population mean is in the interval. B) The population mean is not in the interval. C) The likelihood that any confidence interval based on a sample of 400 graduates will contain the population mean is 0.95. D) There is a 95% chance that the computed interval does not contain the population mean.

662)

The z-value associated with a 90% level of confidence is: A) 1.96 B) 1.645 C) 2.33 D) 2.575 E) 1.28

663)

The z-value associated with a 94% level of confidence is: A) 1.96 B) 1.645 C) 2.33 D) 2.575 E) 1.88

664)

The z-value associated with a 96% level of confidence is: A) 1.96 B) 1.645 C) 2.33 D) 2.05 E) 1.28

665)

The z-value associated with an 80% level of confidence is: A) 1.96 B) 1.645 C) 2.33 D) 2.575 E) 1.28

666)

A random sample of 85 group leaders, supervisors and similar personnel revealed that on the average a person spent 6.5 years on the job before being promoted. The standard deviation of the population was 1.7 years.

666.1) Find the 95% confidence interval for the population mean. A) 6.99 and 7.99 B) 4.15 and 7.15 C) 6.14 and 6.86 D) 6.49 and 7.49

666.2) What is the 95% confidence interval for the true population mean? A) 6.46 and 6.54 B) 3.17 and 9.83 C) 6.13 and 6.87 D) 6.20 and 6.70 E) 6.32 and 6.88

667)

A sample of 25 is selected from a known population of 100 elements. What is the finite population correction factor? A) 8.66 B) 75 C) 0.87 D) Cannot be determined from the information given.

668)

A sample of 50 is selected from a known population of 250 elements. The population standard deviation is 15. What is the standard error of the sample means using the finite population correction factor? A) 2.89 B) 1.90 C) 2.12 D) 13.44 E) Cannot be determined from information given.

669)

Recently, a university surveyed recent graduates of the English Department for their starting salaries. Four hundred graduates returned the survey. The average salary was $55,000 with a standard deviation of $2,500.

669.1) What is the best point estimate of the population mean? A) $55,000 B) $52,500 C) 400 D) $62.5

669.2) What is the 95% confidence interval for the mean salary of all graduates from the English

Department? A) 52,500, $57,500 B) 54,755, $55,245 C) 54,988, $55,012 D) 54,600, $55,600

669.3) What is the 90% confidence interval for the mean salary of all graduates from the English

Department? A) 5,497, $55,039 B) 54,794, $55,206 C) 54,671, $55,329 D) 54,961, $5,539 E) 54,800, $55,200

670)

A survey 144 retail stores revealed that the average price of a ZBox was $375 with a standard error of $20.

670.1) What is the 95% confidence interval to estimate the true cost of the ZBox? A) $323.40 to $426.60 B) $335.47 to $414.53 C) $335.00 to $415.00 D) $335.80 to $414.20

670.2) What is the 99% confidence interval to estimate the true cost of the ZBox? A) $322.79 to $427.21 B) $328.40 to $421.60 C) $335.00 to $415.00 D) $335.80 to $414.20

670.3) If 90% and 95% confidence intervals were developed to estimate the true cost of the

ZBox, what similarities would they have? A) Point estimates B) t-values would be the same C) Standard errors D) Both point estimates and standard errors would be the same E) Both standard errors t-values would be the same

670.4) If 95% and 98% confidence intervals were developed to estimate the true cost of the

ZBox, what differences would they have? A) Standard errors B) Interval widths C) Z-values D) Both standard errors and interval widths E) Both interval widths and t-values

671)

A survey of 25 grocery stores revealed that the average price of a 4-litre bag of milk was $4.98 with a standard error of $0.10.

671.1) What is the 95% confidence interval to estimate the true cost of a 4-litre bag of milk? A) $4.00 to $5.00 B) $4.97 to $4.99 C) $4.77 to $5.19 D) $4.70 to $5.26 E) $4.73 to $5.23

671.2) What is the 98% confidence interval to estimate the true cost of a 4-litre bag of milk? A) $4.00 to $5.00 B) $4.97 to $4.99 C) $4.77 to $5.19 D) $4.70 to $5.26 E) $4.73 to $5.23

671.3) If 90% and 95% confidence intervals were developed to estimate the true cost of a 4-litre

bag of milk, what similarities would they have? A) Point estimates B) t-statistics C) Standard errors D) Both the same point estimate and the same standard error E) Both the same t-statistic and point estimate

672)

Dr. Patton is a professor of English. Recently she counted the number of misspelled words in a group of student essays. She noted the distribution of misspelled words per essay followed the normal distribution with a standard deviation of 2.44 words per essay. For her Tuesday class of 50 students, the mean number of misspelled words per essay was 6.05.

672.1) Construct a 95% confidence interval for the mean number of misspelled words in the

population of student essays. A) 5.374 to 6.726 B) 5.161 to 6.939 C) 5.102 to 6.998 D) 5.482 to 6.618 E) 5.445 to 6.3655

672.2) Construct a 99% confidence interval for the mean number of misspelled words in the

population of student essays. A) 5.374 to 6.726 B) 5.161 to 6.940 C) 5.102 to 6.998 D) 5.482 to 6.618 E) 5.445 to 6.3655

672.3) Construct a 90% confidence interval for the mean number of misspelled words in the

population of student essays. A) 5.374 to 6.726 B) 5.161 to 6.939 C) 5.102 to 6.998 D) 5.482 to 6.618 E) 5.446 to 6.654

672.4) Construct a 92% confidence interval for the mean number of misspelled words in the

population of student essays. A) 5.374 to 6.726 B) 5.161 to 6.939 C) 5.102 to 6.998 D) 5.482 to 6.618 E) 5.446 to 6.6554

673)

i. The t distribution is based on the assumption that the population of interest is normal or nearly normal. ii. The t distribution is a continuous distribution. iii. There is not one t distribution, but rather a "family" of t distributions. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

674)

i. The t distribution is based on the assumption that the population of interest is normal or nearly normal. ii. The t distribution is a discrete distribution. iii. There is not one t distribution, but rather a "family" of t distributions. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

675)

i. The t distribution is positively skewed. ii. All t distributions have the same mean of zero and a standard deviation of 1. iii. The t distribution is more spread out and flatter at the center than is the standard normal distribution. However, as the sample size increases, the t distribution curve approaches the standard normal distribution. A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement but not (i) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

676)

i. The Student t distribution has a greater spread than does the z distribution. As a result, the critical values of t for a given level of significance are larger in magnitude than the corresponding z critical values. ii. The test statistic t has n-1 degrees of freedom. iii. William S. Gosset, a brewmaster, developed the t test for the Guinness Brewery in Ireland, who published it in 1908 using the pen name "Student." A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement but not (i) or (ii). C) (i) and,(iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

677)

i. The test statistic t has n-1 degrees of freedom. ii. All t distributions have the same mean of zero and a standard deviation of 1. iii. The t distribution is more spread out and flatter at the center than is the standard normal distribution. However, as the sample size increases, the t distribution curve approaches the standard normal distribution. A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement but not (i) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

678)

i. The test statistic for a problem involving an unknown population standard deviation is the Student's t distribution. ii. The t distribution approaches the Z distribution as the sample size increases. iii. As the sample size increases, the computed value of t decreases. A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement but not (i) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

679)

Which statement is correct about the t distribution? A) Mean = 0 B) Symmetric C) Based on degrees of freedom D) Mean = 0, symmetric and based on degrees of freedom E) Mean = 0 and symmetric

680)

What kind of distribution is the t distribution? A) Continuous B) Discrete C) Subjective D) Standard

681)

How does the t distribution differ from the standard z distribution? A) Continuous distribution B) Bell-shaped C) Family of distributions D) Symmetrical

682)

A sample of 20 is selected from the population. What is the number of degrees of freedom used to determine the appropriate critical t-value? A) 20 B) 19 C) 21 D) 25

683)

The t distribution is similar to the z distribution in all BUT ONE of the following characteristics. Which one is it? A) Continuous B) Symmetrical C) Bell-shaped D) t distribution's mean = 0 and standard deviation = 1

684)

Student's t is used when A) the sample is more than 30 observations. B) the sample size is ≤ 5% of the population. C) the population standard deviation is unknown. D) any time.

685)

The distribution of Student's t has A) a mean of zero and a standard deviation of one. B) a mean of one and a standard deviation of one. C) a mean of zero and a standard deviation that depends on the sample size. D) a mean that depends on the sample size and a standard deviation of one.

686)

The distribution of Student's t is A) symmetrical. B) negatively skewed. C) positively skewed. D) a discrete probability distribution.

687)

When using Student's t to compute an interval estimate, A) we assume that the samples are collected from normally distributed populations. B) we estimate the population standard deviation based on the sample standard deviation. C) use the z distribution. D) we assume that samples are collected from normally distributed populations and the estimate of the population standard deviation based on the sample standard deviation. E) we assume that the samples are collected from normally distributed populations and use the z distribution.

688)

The t distribution approaches __________ as the sample size increases. As the sample size increases, the computed value of t _________. A) Z distribution; decreases B) Z distribution; increases C) Z distribution; stays the same D) 0; decreases E) 0; increases

689)

In order to construct a 90% confidence interval for the population mean when the population standard deviation is unknown and the sample size is 18, you should use the tvalue indicated as: A) t0.10,18 B) t 0.10,17 C) t0.05,18 D) t0.05,17 E) t0.90,17

690)

In order to construct a 95% confidence interval for the population mean when the population standard deviation is unknown and the sample size is 15, you should use the tvalue indicated as: A) t0.10,15 B) t0.10,14 C) t0.05,15 D) t0.05,14 E) t0.025,14

691)

A student wanted to quickly construct a 95% confidence interval for the average age of students in her statistics class. She randomly selected 9 students. Their average age was 19.1 years with a standard deviation of 1.5 years.

691.1) What is the best point estimate for the population mean? A) 2.1 years B) 1.5 years C) 19.1 years D) 9 years E) 17.6 years

691.2) What is the 95% confidence interval for the population mean? A) [0.97, 3.27] B) [15.64, 22.56] C) [17.97, 20.23] D) [17.95, 20.25] E) [17.42, 20.78]

691.3) What is the 99% confidence interval for the population mean? A) [17.42, 20.78] B) [17.48, 20.72] C) [14.23, 23.98] D) [0.44, 3.80] E) [17.95, 20.25]

692)

A sample of 100 students is selected from a known population of 1,000 students to construct a 95% confidence interval for the average SAT score. What correction factor should be used to compute the standard error? A) 0.949 B) 0.901 C) 1.96 D) 9.01 E) Cannot be determined

693)

A manager of a local store wants to estimate the mean amount spent per shopping visit by customers. Summary statistics from a sample taken reveal the following: Descriptive statistics Shopping Expenditures count

mean

49.3440

sample variance

81.2645

sample standard deviation

9.0147

minimum

23.78

maximum

61.83

range

38.05

standard error of the mean

2.0157

693.1) Determine a 95% confidence interval for the mean amount spent. A) [45.21, 53.56] B) [40.36, 58.35] C) [30.54, 68.14] D) [45.13, 53.56] E) [29.34, 69.34]

693.2) If 90% and 95% confidence intervals were developed to estimate the true shopping

expenditure, what similarities would exist? A) Point estimates B) t-values would be the same C) Standard errors D) Both point estimates and standard errors E) Both point estimates and t-values

693.3) If 95% and 98% confidence intervals were developed to estimate the true shopping

expenditure, what differences would exist? A) Standard errors B) Interval widths C) t-values D) Both interval widths and t-values E) Both standard errors and interval widths

693.4) The store manager wonders whether the population mean could have been $50 or $60. A) Since $60 is within the 95% confidence interval, the population mean is likely to be

$60. B) Since $60 is not within the 95% confidence interval, the population mean is not likely to be $60. C) Since $50 is within the 95% confidence interval, the population mean is likely to be $50. D) Since $50 is not within the 95% confidence interval, the population mean is not likely to be $50. E) Since $60 is not within the 95% confidence interval, the population mean is not likely to be $60; however, it is likely to be $50.

694)

A statistics professor wishes to estimate the average mark on a term test for a course that has multiple sections and many students. A survey of some of the students registered for the course reveals the following results: Descriptive statistics Class Grades count

mean

70.81

sample variance

520.15

sample standard deviation

22.81

minimum

14.3

maximum

99.2

range

84.9

standard error of the mean

4.03

694.1) Determine a 95% confidence interval for the term test results. A) [48.0, 93.6] B) [66.8, 74.8] C) [62.9, 78.71] D) [64.2, 77.3] E) [62.6, 79.0]

694.2) Determine a 98% confidence interval for the term test results. A) [48.0, 93.6] B) [66.8, 74.8] C) [62.9, 78.71] D) [64.2, 77.3] E) [60.9, 80.7]

694.3) If 90% and 95% confidence intervals were developed to estimate the true term test mean,

what similarities would exist? A) Point estimates B) t-values C) Standard errors D) Both point estimates and standard errors E) No similarities with point estimates, t-values or standard errors

694.4) If 95% and 98% confidence intervals were developed to estimate the true term test mean,

what differences would exist? A) Standard errors B) Interval widths C) t-values D) Both interval widths and t-values

694.5) The student from the course wonders whether the population mean could have been 75 or

80. A) Since 80 is within the 95% confidence interval, the population mean is likely to be

80. B) Since 80 is not within the 95% confidence interval, the population mean is not likely to be 80. C) Since 75 is within the 95% confidence interval, the population mean is likely to be 75. D) Since neither 75 nor 80 is within the 95% confidence interval, the population mean is not likely to be 75 or 80. E) Since 80 is not within the 95% confidence interval, the population mean is not likely to be 80, but it is likely to be 75.

694.6) The student from the course wonders whether the population mean could have been 60 or

80. A) Since 80 is within the 95% confidence interval, the population mean is likely to be

80. B) Since 80 is not within the 95% confidence interval, the population mean is not likely to be 80. C) Since 60 is within the 95% confidence interval, the population mean is likely to be 60. D) Since neither 60 nor 80 is within the 95% confidence interval, the population mean is not likely to be 60 or 80.

695)

The following summarizes the amount of snowfall in Ontario over the past number of years. Descriptive statistics #1 count

mean

1,871.95

sample variance

433,712.90

sample standard deviation

658.57

minimum

526

maximum

3693

range

3167

standard error of the mean

88.80

695.1) Determine a 95% confidence interval for the average annual snowfall. A) [1,698, 2,046] B) [1,665, 2,079] C) [1,213, 2,531] D) [1,783, 1,961] E) [1694, 2050]

695.2) Determine a 98% confidence interval for the average annual snowfall. A) [1698, 2046] B) [1665, 2079] C) [1213, 2531] D) [1783, 1961] E) [1659, 2085]

695.3) If 90% and 95% confidence intervals were developed to estimate the true average annual

snowfall, what similarities would they have? A) Point estimates B) t-values C) Standard errors D) Both point estimates and standard errors E) Both point estimates and t-Values

695.4) If 95% and 98% confidence intervals were developed to estimate the true average annual

snowfall, what differences would exist? A) Standard errors B) Interval widths C) t-values D) Both interval widths and t-values

695.5) You wonder whether the population mean could have been 2000 or 1900. A) Since 1900 is within the 95% confidence interval, the population mean is likely to be

1900. B) Since 1900 is within the 95% confidence interval, the population mean is not likely to be 1900. C) Since 2000 is within the 95% confidence interval, the population mean is likely to be 2000. D) Since neither 1900 nor 200 is within the 95% confidence interval, the population mean is not likely to be 1900 or 2000. E) Since 1900 and 2000 are both within the 95% confidence interval, the population mean is likely to be either value.

695.6) You wonder whether the population mean could have been 1,600 or 2,100. A) Since 1600 is within the 95% confidence interval, the population mean is likely to be

1,600. B) Since 1600 is not within the 95% confidence interval, the population mean is not likely to be 1,600. C) Since 2100 is within the 95% confidence interval, the population mean is likely to be 2,100. D) Since neither 1,600 nor 2,100 is within the 95% confidence interval, the population mean is not likely to be 1,600 or 2000. E) Since 1900 and 2000 are both within the 95% confidence interval, the population mean is likely to be either value.

696)

The following summarizes the average price of SafeFare Canada stock at the end of 20 randomly selected weeks in 2021. SafeFare Canada Mean

17.4

Standard Error

0.55

Median

17.5

Mode

19.4

Standard Deviation

2.48

Sample Variance

6.168

Kurtosis

-0.245

Skewness

-0.535

Range

9.25

Minimum

11.5

Maximum

20.75

Sum

347.75

Count

Confidence Level (90.0%)

0.960303

696.1) Determine a 90% confidence interval for the average Safefare stock price in 2021. A) [16.44, 18.36] B) [14.90, 19.87] C) [17.48, 19.40] D) [16.43, 18.35] E) Unable to determine from the information given

696.2) Determine a 95% confidence interval for the average SafeFair stock price in 2021. A) [16.83, 17.42] B) [14.90, 19.87] C) [17.48, 19.40] D) [16.24, 18.56] E) [16.23, 18.55]

696.3) Determine a 98% confidence interval for the average Safefare stock price in 2021.. A) [16.83, 17.42] B) [14.90, 19.87] C) [17.48, 19.40] D) [16.24, 18.56] E) [15.99,18.81]

697)

A pharmaceutical company wanted to estimate the population mean of monthly sales for their 250 sales people. Forty sales people were randomly selected. Their mean monthly sales were $10,000 with a standard deviation of $1,000. Construct a 95% confidence interval for the population mean. A) [9,690.1, 10,309.9] B) [9706.3, 10293.8] C) [8,040, 11,960] D) [8,000, 12,000] E) [9,000, 11,000]

698)

The mean weight of trucks traveling on a particular section of Highway 401 is not known. A provincial highway inspector needs an estimate of the mean. He selects a random sample of 49 trucks passing the weighing station and finds the mean is 15.8 tons, with a standard deviation of the sample of 3.8 tons. What is the 95 percent interval for the population mean? A) 14.7 and 16.9 B) 13.2 and 17.6 C) 10.0 and 20.0 D) 16.1 and 18.1

699)

The Sugar Producers Association wants to estimate the mean yearly sugar consumption. A sample of 16 people reveals the mean yearly consumption to be 27 kg with a sample standard deviation of 9 kg. Assume it follows a normal population.

699.1) For a 90% confidence interval, what is the critical value needed? A) t = 1.753 B) t = 2.131 C) t = 2.947 D) z = 1.645 E) z = 1.96

699.2) For a 95% confidence interval, what is the critical value needed? A) t = 1.753 B) t = 2.131 C) t = 2.947 D) z = 1.645 E) z = 1.96

699.3) For a 99% confidence interval, what is the critical value needed? A) t = 1.753 B) t = 2.131 C) t = 2.947 D) z = 1.645 E) z = 1.96

699.4) Develop a 90% confidence interval for the mean annual consumption of sugar. A) 23.06 to 30.94 B) 22.20 to 31.80 C) 20.37 to 33.63 D) 23.30 to 30.70 E) 23.0 to 30.0

699.5) Develop a 95% confidence interval for the mean annual consumption of sugar. A) 23.06 to 30.94 B) 22.20 to 31.80 C) 20.37 to 33.63 D) 23.30 to 30.70 E) 23.0 to 30.0

699.6) Develop a 99% confidence interval for the mean annual consumption of sugar. A) 23.06 to 30.94 B) 22.20 to 31.80 C) 20.37 to 33.63 D) 23.30 to 30.70 E) 23.0 to 30.0

700)

The Sugar Producers Association wants to estimate the mean yearly sugar consumption. A sample of 25 people reveals the mean yearly consumption to be 27 kg with a sample standard deviation of 9 kg. Assume it follows a normal population.

700.1) For a 90% confidence interval, what is the critical value needed? A) t = 1.708 B) t = 1.711 C) t = 2.797 D) z = 1.645 E) z = 1.96

700.2) For a 99% confidence interval, what is the critical value needed? A) t = 1.708 B) t = 1.711 C) t = 2.797 D) z = 1.645 E) z = 1.96

700.3) 87 For a 95% confidence interval, what is the critical value needed? A) t = 2.787 B) t = 2.064 C) t = 2.797 D) z = 1.645 E) z = 1.96

700.4) Develop a 90% confidence interval for the mean annual consumption of sugar. A) 23.06 to 30.94 B) 23.285 to 30.715 C) 21.97 to 32.03 D) 23.30 to 30.70 E) 23.92 to 30.08

700.5) Develop a 95% confidence interval for the mean annual consumption of sugar. A) 23.06 to 30.94 B) 23.285 to 30.715 C) 21.97 to 32.03 D) 23.30 to 30.70 E) 23.92 to 30.08

700.6) Develop a 99% confidence interval for the mean annual consumption of sugar. A) 23.06 to 30.94 B) 23.285 to 30.715 C) 21.97 to 32.03 D) 23.30 to 30.70 E) 23.92 to 30.08

701)

The Dean of the Business School wants to estimate the mean number of hours worked per week by students. A sample of only 12 students showed a mean of 24 hours with a standard deviation of 4 hours. Find the 95 percent confidence interval for the population mean. A) 21.46 and 26.54 B) 21.17 and 26.45 C) 22.88 and 25.12 D) 21.07 and 26.07 E) 21.93 and 26.07

702)

The manager of the college cafeteria wants to estimate the mean amount spent per customer per purchase. A sample of 10 customers revealed the following amounts spent: $4.45

$4.05

$4.95

$3.25

$4.68

$5.75

$6.01

$3.99

$5.25

$2.95

Find the 99 percent confidence limits for the mean amount spent. Sample mean = $4.53, s = $1.00 A) 3.53 and 5.53 B) 3.50 and 5.56 C) 3.48 and 5.58 D) 3.84 and 5.85 E) 3.35 and 5.35

703)

A sample of 500 executives who own their own home revealed 175 planned to sell their homes and retire to Victoria. Develop a 98% confidence interval for the proportion of executives that plan to sell and move to Victoria. A) 30% and 40% B) 29% and 41% C) 28% and 42% D) 29.5% and 40.5% E) 29.3% and 41.3%

704)

College X is concerned about their employees making use of their email for non-business purposes. A random sample of 400 e-mails discovered 80 messages that were not business related.

704.1) The 95% confidence interval for the population proportion is: A) 0.167 to 0.233 B) 0.161 to 0.239 C) 0.148 to 0.252 D) 0.186 to 0.254 E) 0.179 to 0.261

704.2) The 99% confidence interval for the population proportion is: A) 0.167 to 0.233 B) 0.161 to 0.239 C) 0.148 to 0.252 D) 0.186 to 0.254 E) 0.179 to 0.261

704.3) The 90% confidence interval for the population proportion is: A) 0.167 to 0.233 B) 0.161 to 0.239 C) 0.148 to 0.252 D) 0.186 to 0.254 E) 0.179 to 0.261

705)

College X is concerned about their employees making use of their email for non-business purposes. A random sample of 400 e-mails discovered 60 messages that were not business related.

705.1) The 99% confidence interval for the population proportion is: A) 0.104 to 0.196 B) 0.115 to 0.185 C) 0.148 to 0.252 D) 0.121 to 0.179 E) 0.186 to 0.254

705.2) The 95% confidence interval for the population proportion is: A) 0.104 to 0.196 B) 0.115 to 0.185 C) 0.148 to 0.252 D) 0.121 to 0.179 E) 0.186 to 0.254

705.3) The 90% confidence interval for the population proportion is: A) 0.104 to 0.196 B) 0.115 to 0.185 C) 0.148 to 0.252 D) 0.121 to 0.179 E) 0.186 to 0.254

706)

Suppose 1,600 of 2,000 registered voters sampled said they planned to vote for a particular candidate. Using the 0.95 degree of confidence, what is the interval estimate for the population proportion (to the nearest tenth of a percent)? A) 78.2% to 81.8% B) 69.2% to 86.4% C) 76.5% to 83.5% D) 77.7% to 82.3%

707)

A sample of union members was selected and their opinions regarding the proposed management union contract were recorded with 1,600 out of the 2,000 members in favour of it. Using a 95% confidence level, the interval estimate for the population proportion was computed to be 0.78 and 0.82. A) This indicates that about 68 out of 100 similarly constructed intervals would include the population proportion. B) This indicates that about 95 out of 100 similarly constructed intervals would include the population proportion. C) This indicates that about 99 out of 100 similarly constructed intervals would include the population proportion. D) This indicates that about 78 out of 100 similarly constructed intervals would include the population proportion.

708)

There are 2,000 eligible voters in a precinct. Despite protests from knowledgeable persons that a sample size of 500 was too large in relation to the total, the 500 selected at random were asked to indicate whether they planned to vote for the Liberal incumbent or the Conservative challenger. Of the 500 surveyed, 350 said they were going to vote for the Liberal incumbent. Using the 0.99 confidence coefficient, what are the confidence limits for the proportion that plan to vote for the Liberal incumbent? A) 0.060 and 0.700 B) 0.612 and 0.712 C) 0.397 and 0.797 D) 0.826 and 0.926 E) 0.6542 and 0.7458

709)

If 2,000 card-carrying members of a political party were randomly sampled, and 1,600 said they wanted a change in leadership, what is the 95% confidence interval for the true population percentage for all of the card-carrying members of the party who wanted a change in leadership? A) 78.2% to 81.8% B) 78.0% to 82.0% C) 76.5% to 83.5% D) 77.7% to 82.3% E) less than 50%

710)

A financial analyst wanted to determine the mean annual return on mutual funds. A random sample of 60 returns shows a mean of 12%. If the population standard deviation is assumed to be 4%, estimate with 95% confidence the mean annual return on all mutual funds. A) 11.325% to 13.012% B) 10.988% to 14.025% C) 11.325% to 14.025% D) 10.988% to 13.012% E) 8% to 16%

711)

A survey of an urban university (population of 25,450) showed that 870 of 1,100 students sampled supported a fee increase to fund improvements to the student recreation center.

711.1) Using the 95% level of confidence, what is the confidence interval? A) [0.767, 0.814] B) [0.759, 0.822] C) [0.771, 0.811] D) [0.714, 0.866]

711.2) Using the 99% level of confidence, what is the confidence interval? A) [0.751, 0.829] B) [0.760, 0.822] C) [0.767, 0.814] D) [0.771, 0.811]

711.3) If university officials say that at least 70% of the voting student population support the

fee increase, what conclusion can be drawn based on a 95% level of confidence? A) 70% is not in the interval, need to take another sample. B) 70% is not in the interval, so assume it will not be supported. C) 70% is below the interval, so assume it will be supported. D) Since this was not based on population, cannot make conclusion.

712)

College X is concerned about their employees making use of their email for non-business purposes. A random sample of 400 e-mails discovered 40 messages that were not business related. The 95% confidence interval for the population proportion is: A) 0.199 to 0.201 B) 0.101 to 0.199 C) 0.07060 to0.12940 D) 0.0753 to 0.1247 E) 0.0700 to 0.1000

713)

College X is concerned about their employees making use of their email for non-business purposes. A random sample of 400 e-mails discovered 70 messages that were not business related. The 95% confidence interval for the population proportion is: A) 0.1378 to 0.2122 B) 0.101 to 0.199 C) 0.1206 to.1902 D) 0.0753 to 0.1247 E) 0.1300 to 0.2100

714)

A consumer group would like to estimate the mean monthly electricity charge for a single family house in July (within $5) using a 99 percent level of confidence. Based on similar studies the standard deviation is estimated to be $20.00. How large a sample is required? A) 105 B) 106 C) 107 D) 108 E) 109

715)

The Kennel Club wants to estimate the proportion of children that have a dog as a pet. Assume a 95% level of confidence and that the club estimates that 30% of the children have a dog as a pet. If the club wants the estimate to be within 3% of the population proportion, how many children would they need to contact? A) 978 B) 879 C) 789 D) 987 E) 897

716)

College X is concerned about their employees making use of their email for non-business purposes. You have been approached to assist in this matter. College X decides on a 95% confidence level and state that the estimation proportion must be within 2 percent of the population proportion. A pilot survey reveals that 8 out of 50 emails sampled were not for business purposes. How many emails should be surveyed to meet your requirements? A) 1,291 B) 707 C) 498 D) 2,230 E) 1,000

717)

College X is concerned about their employees making use of their email for non-business purposes. You have been approached to assist in this matter. College X decides on a 90% confidence level and state that the estimation proportion must be within 2 percent of the population proportion. A pilot survey reveals that 8 out of 50 emails sampled were not for business purposes. How many emails should be surveyed to meet your requirements? A) 910 B) 707 C) 498 D) 1,221 E) 1,000

718)

College X is concerned about their employees making use of their email for non-business purposes. You have been approached to assist in this matter. College X decides on a 99% confidence level and state that the estimation proportion must be within 2 percent of the population proportion. A pilot survey reveals that 8 out of 50 emails sampled were not for business purposes. How many emails should be surveyed to meet your requirements? A) 910 B) 2,100 C) 498 D) 1,221 E) 2,228

719)

College X is concerned about their employees making use of their email for non-business purposes. You have been approached to assist in this matter. College X decides on a 90% confidence level and state that the estimation proportion must be within 2 percent of the population proportion. A pilot survey reveals that 10 out of 50 emails sampled were not for business purposes. How many emails should be surveyed to meet your requirements? A) 910 B) 1,537 C) 1,083 D) 1,221 E) 2,654

720)

College X is concerned about their employees making use of their email for non-business purposes. You have been approached to assist in this matter. College X decides on a 95% confidence level and state that the estimation proportion must be within 2 percent of the population proportion. A pilot survey reveals that 10 out of 50 emails sampled were not for business purposes. How many emails should be surveyed to meet your requirements? A) 910 B) 1,537 C) 1,083 D) 1,221 E) 2,654

721)

College X is concerned about their employees making use of their email for non-business purposes. You have been approached to assist in this matter. College X decides on a 99% confidence level and state that the estimation proportion must be within 2 percent of the population proportion. A pilot survey reveals that 10 out of 50 emails sampled were not for business purposes. How many emails should be surveyed to meet your requirements? A) 910 B) 1,537 C) 1,083 D) 1,221 E) 2,653

722)

A group of statistics students decided to conduct a survey at their university to find the average (mean) amount of time students spent studying per week. Assuming a standard deviation of 6 hours, what is the required sample size if the error is to be less than ½ hour with a 95% level of confidence? A) 554 B) 130 C) 35 D) 393

723)

A group of statistics students decided to conduct a survey at their university to find the average (mean) amount of time students spent studying per week. Assuming a standard deviation of 3 hours, what is the required sample size if the error is to be less than ½ hour with a 99% level of confidence? A) 196 B) 239 C) 15 D) 16

724)

i. One factor in determining the size of a sample is the degree of confidence selected. This is usually 0.95 or 0.99, but it may be any degree of confidence you specify. ii. One factor in determining the size of a sample is the maximum allowable error that you must decide on. It is the maximum error you will tolerate at a specified level of confidence. iii. The variation in the population as measured by the standard deviation has little or no effect in determining the size of a sample selected from the population. A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement but not (i) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

725)

i. The higher the degree of confidence, the larger the sample required to give a certain precision. ii. To determine the size of a sample, the standard deviation of the population must be estimated by either taking a pilot survey or by approximating it based on knowledge of the population. iii. One factor in determining the size of a sample is the maximum allowable error that you must decide on. It is the maximum error you will tolerate at a specified level of confidence. A) (i), (ii), and (iii) are all correct statements. B) (iii) is a correct statement but not (i) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

726)

The mean number of travel days per year for the outside salespeople employed by hardware distributors is to be estimated. The 0.90 degree of confidence is to be used. The mean of a small pilot study was 150 days, with a standard deviation of 14 days. If the population mean is to be estimated within two days, how many outside salespeople should be sampled? A) 133 B) 452 C) 511 D) 2,100

727)

The proportion of junior executives leaving large manufacturing companies within three years is to be estimated within 3 percent. The 0.95 degree of confidence is to be used. A study conducted several years ago revealed that the percent of junior executives leaving within three years was 21. To update this study, the files of how many junior executives should be studied? A) 594 B) 612 C) 709 D) 897

728)

How large a sample of government employees should be taken if we want to estimate with 98% confidence the mean salary to within $2,000? The population standard deviation is assumed to be $10,500. (Round up to the nearest whole number) A) 150 B) 200 C) 525 D) 100 E) 75

729)

Determine the sample size that is required to estimate a population mean to within 0.4 units with a 99% confidence when the population standard deviation is 1.75. A) 172 B) 127 C) 217 D) 61 E) Over 500

730)

The sample size needed to estimate a population mean within 2 units with a 95% confidence when the population standard deviation equals 8 is A) 9 B) 61 C) 62 D) 8 E) 50

731)

A bank wishes to estimate the mean balances owed by customers holding MasterCard. The population standard deviation is estimated to be $300. If a 98 percent confidence interval is used and an interval within $75 is desired, how many cardholders should be sampled? A) 44 B) 212 C) 629 D) 87

732)

Which of the following is NOT necessary to determine how large a sample to select from a population? A) Level of confidence in estimating the population parameter B) Size of the population C) Maximum allowable error in estimating the population parameter D) Estimate of the population variation

733)

(i) The interval estimate states the range within which a population parameter probably lies. (ii). The measure of confidence that one has in the interval estimate is called degree of level of confidence. (iii) For a sampling distribution of the means, 95% percent of the means would be between ± 1.96 standard deviations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

734)

(i) The interval estimate states the range within which a population parameter probably lies. (ii) The confidence interval is the interval within which a population parameter is expected to lie. (iii) For a sampling distribution of the means, 95% percent of the means would be between ± 1.96 standard deviations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

735)

(i) The point estimate states the range within which a population parameter probably lies. (ii). The measure of confidence that one has in the interval estimate is called degree of level of confidence. (iii) For a sampling distribution of the means, 95% percent of the means would be between ± 1.96 standard deviations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

736)

(i) Reasoning from a sample or small group to the entire group or population is called statistical inference. (ii) A 95 percent confidence interval implies that about 95 out of 100 similarly constructed intervals will include the parameter being estimated. (iii) For a sampling distribution of the means, 95% percent of the means would be between ± 1.96 standard deviations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

737)

(i) The interval estimate states the range within which a population parameter probably lies. (ii) A 95 percent confidence interval implies that about 95 out of 100 similarly constructed intervals will include the parameter being estimated. (iii) For a sampling distribution of the means, 95% percent of the means would be between ± 1.96 standard deviations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

738)

From a sample of 100 students, the mean number of time streaming Netflix, Prime, Crave etc. per week is 15.5 hours with a standard deviation 6.5 hours.

738.1) Determine the standard error. A) 0.065 B) 0.155 C) 0.65 D) 1.55

738.2) Using an 80% confidence level, what is the t-value? A) 1.280 B) 1.290 C) 1.645 D) 1.660

738.3) Using an 90% confidence level, what is the t-value? A) 1.280 B) 1.29 C) 1.645 D) 1.660

739)

From a sample of 30 students, the mean number of time streaming Netflix, Prime and Crave etc. per week is 15.5 hours with a standard deviation 6.5 hours.

739.1) What is the 80% confidence interval for the true population mean streaming time for all

students? A) 13.9 to 17.1 B) 13.5 to 17.5 C) 13.1 to 17.9 D) 12.2 to 18.8

739.2) What is the 90% confidence interval for the true population mean streaming time for all

students? A) 13.9 to 17.1 B) 13.5 to 17.5 C) 13.1 to 17.9 D) 12.2 to 18.8

739.3) What is the 95% confidence interval for the true population mean streaming time for all

students? A) 13.9 to 17.1 B) 13.5 to 17.5 C) 13.1 to 17.9 D) 12.2 to 18.8

739.4) What is the 99% confidence interval for the true population mean streaming time for all

students? A) 13.9 to 17.1 B) 13.5 to 17.5 C) 13.1 to 17.9 D) 12.2 to 18.8

740)

From a sample of 40 students, the mean number of time streaming Netflix, Prime, and Crave etc. per week is 15.5 hours with a standard deviation 6.5 hours. What is the 95% confidence interval for the true population mean streaming time for all students? A) 13.4 to 17.6 B) 13.8 to 17.2 C) 14.1 to 16.9 D) 14.2 to 16.8

741)

From a sample of 60 students, the mean number of time streaming Netflix, Prime, and Crave etc. per week is 15.5 hours with a standard deviation 6.5 hours. What is the 95% confidence interval for the true population mean streaming time for all students? A) 13.4 to 17.6 B) 13.8 to 17.2 C) 14.1 to 16.9 D) 14.2 to 16.8

742)

From a sample of 80 students, the mean number of time streaming Netflix, Prime, and Crave etc. per week is 15.5 hours with a standard deviation 6.5 hours. What is the 95% confidence interval for the true population mean streaming time for all students? A) 13.4 to 17.6 B) 13.8 to 17.2 C) 14.1 to 16.9 D) 14.2 to 16.8

743)

From a sample of 100 students, the mean number of time streaming Netflix, Prime, and Crave etc. per week is 15.5 hours with a standard deviation 6.5 hours. What is the 95% confidence interval for the true population mean streaming time for all students? A) 13.4 to 17.6 B) 13.8 to 17.2 C) 14.1 to 16.9 D) 14.2 to 16.8

744)

In a survey of 100 consumers, 60 stated that the next vehicle they purchase will be an electric vehicle.

744.1) Find an 80% confidence interval of the true % of consumers who plan to purchase an

electrical vehicle next. A) 53.7% to 66.3% B) 51.9% to 68.1% C) 50.4% to 69.6% D) 47.4% to 72.6%

744.2) Find a 90% confidence interval of the true % of consumers who plan to purchase an

electrical vehicle next. A) 53.7% to 66.3% B) 51.9% to 68.1% C) 50.4% to 69.6% D) 47.4% to 72.6%

744.3) Find a 95% confidence interval of the true % of consumers who plan to purchase an

electrical vehicle next. A) 53.7% to 66.3% B) 51.9% to 68.1% C) 50.4% to 69.6% D) 47.4% to 72.6%

744.4) Find a 99% confidence interval of the true % of consumers who plan to purchase an

electrical vehicle next. A) 53.7% to 66.3% B) 51.9% to 68.1% C) 50.4% to 69.6% D) 47.4% to 72.6%

745)

Due to the numerous lockdowns during the pandemic, a researcher would like to find out the average weight gain of people over this period. The results of a pilot survey indicate the standard deviation is 7.8 pounds.

745.1) How many people should be in the sample if you would like to be 95% confident of the

results and be within 2.5 pounds of the actual mean? A) 38 B) 59 C) 104 D) 234

745.2) How many people should be in the sample if you would like to be 95% confident of the

results and be within 2 pounds of the actual mean? A) 38 B) 59 C) 104 D) 234

745.3) How many people should be in the sample if you would like to be 95% confident of the

results and be within 1.5 pounds of the actual mean? A) 38 B) 59 C) 104 D) 234

745.4) How many people should be in the sample if you would like to be 95% confident of the

results and be within 1 pound of the actual mean? A) 38 B) 59 C) 104 D) 234

Answer Key Test name: chapter 8 63) A 64) C 65) A 66) C 67) D 68) E 69) B 70) C 71) C 72) Section Break 72.1) A 72.2) B 72.3) B 73) C 74) B 75) E 76) D 77) E 78) Section Break 78.1) C 78.2) C 79) C 80) B 81) Section Break 81.1) A 81.2) B 81.3) B 82) Section Break 82.1) B 82.2) A 82.3) D 82.4) E 83) Section Break 83.1) C 83.2) E 83.3) D 84) Section Break

84.1) A 84.2) B 84.3) D 84.4) E 85) A 86) C 87) B 88) A 89) C 90) A 91) D 92) A 93) C 94) B 95) D 96) C 97) C 98) A 99) D 100) B 101) D 102) E 103) Section Break 103.1) C 103.2) D 103.3) A 104) A 105) Section Break 105.1) D 105.2) D 105.3) D 105.4) E 106) Section Break 106.1) E 106.2) E 106.3) D 106.4) D 106.5) E 106.6) D 107) Section Break

107.1) E 107.2) E 107.3) D 107.4) D 107.5) E 107.6) D 108) Section Break 108.1) A 108.2) D 108.3) E 109) B 110) A 111) Section Break 111.1) A 111.2) B 111.3) C 111.4) A 111.5) B 111.6) C 112) Section Break 112.1) B 112.2) C 112.3) B 112.4) E 112.5) B 112.6) C 113) A 114) B 115) A 116) Section Break 116.1) B 116.2) C 116.3) A 117) Section Break 117.1) A 117.2) B 117.3) D 118) A 119) B 120) E

121) A 122) D 123) Section Break 123.1) A 123.2) B 123.3) C 124) C 125) A 126) C 127) E 128) A 129) A 130) E 131) C 132) B 133) E 134) A 135) B 136) D 137) A 138) A 139) C 140) A 141) B 142) C 143) D 144) B 145) A 146) A 147) D 148) A 149) A 150) Section Break 150.1) C 150.2) B 150.3) D 151) Section Break 151.1) A 151.2) B 151.3) C

151.4) D 152) A 153) B 154) C 155) D 156) Section Break 156.1) A 156.2) B 156.3) C 156.4) D 157) Section Break 157.1) A 157.2) B 157.3) C 157.4) D

Student name:__________ 746)

i. Two examples of a hypothesis are: 1) mean monthly income from all sources for senior citizens is $841 and 2) twenty percent of juvenile offenders ultimately are caught and sentenced to prison. ii. Hypothesis testing is a procedure based on sample evidence and probability theory to decide whether the hypothesis is a reasonable statement. iii. Since there is more variability in sample means computed from smaller samples, we have more confidence in the resulting estimates and are less apt to reject null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

747)

i. Two examples of a hypothesis are: 1) mean monthly income from all sources for senior citizens is $841 and 2) twenty percent of juvenile offenders ultimately are caught and sentenced to prison. ii. Hypothesis testing is a procedure based on sample evidence and probability theory to decide whether the hypothesis is a reasonable statement. iii. The test statistic for a problem involving an unknown population standard deviation is the Student's t distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

748)

i. Two examples of a hypothesis are: 1) mean monthly income from all sources for senior citizens is $841 and 2) twenty percent of juvenile offenders ultimately are caught and sentenced to prison. ii. Hypothesis testing is a procedure based on sample evidence and probability theory to decide whether the hypothesis is a reasonable statement. iii. We call a statement about the value of a population parameter a hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

749)

i. Two examples of a hypothesis are: 1) mean monthly income from all sources for senior citizens is $841 and 2) twenty percent of juvenile offenders ultimately are caught and sentenced to prison. ii. Since there is more variability in sample means computed from smaller samples, we have more confidence in the resulting estimates and are less apt to reject null hypothesis. iii. The test statistic for a problem where the population standard deviation is unknown is the Student's t distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

750)

i. Two examples of a hypothesis are: 1) mean monthly income from all sources for senior citizens is $841 and 2) twenty percent of juvenile offenders ultimately are caught and sentenced to prison. ii. Since there is more variability in sample means computed from smaller samples, we have more confidence in the resulting estimates and are less apt to reject null hypothesis. iii. We call a statement about the value of a population parameter a hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

751)

752)

Which of the following does NOT hold true for the t distribution? A) Confidence intervals will be wider than for large samples. B) The region of acceptance will be larger than for large samples. C) A larger computed t value will be needed to reject the null hypothesis than for large samples using z. D) There is only one t distribution.

i. An alternate hypothesis is a statement about a population parameter that is accepted when the null hypothesis is rejected. ii. The level of significance is the risk we assume of rejecting the null hypothesis when it is actually true. iii. There is only one level of significance that is applied to all studies involving sampling. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

753)

i. An alternate hypothesis is a statement about a population parameter that is accepted when the null hypothesis is rejected. ii. The level of significance is the risk we assume of rejecting the null hypothesis when it is actually true. iii. The researcher must decide on the level of significance before formulating a decision rule and collecting sample data. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

754)

i. The level of significance is the risk we assume of rejecting the null hypothesis when it is actually true. ii. There is only one level of significance that is applied to all studies involving sampling. iii. The researcher must decide on the level of significance before formulating a decision rule and collecting sample data. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

755)

i. Two types of possible errors always exist when testing hypotheses—a Type I error, in which the null hypothesis is rejected when it should not have been rejected, and a Type II error in which the null hypothesis is not rejected when it should have been rejected. ii. A test statistic is a value determined from sample information collected to test the null hypothesis. iii. The region or area of rejection defines the location of all those values that are so large or so small that the probability of their occurrence under a true null hypothesis is rather remote. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

756)

i. Two types of possible errors always exist when testing hypotheses—a Type I error, in which the null hypothesis is rejected when it should not have been rejected, and a Type II error in which the null hypothesis is not rejected when it should have been rejected. ii. A test statistic is a value determined from sample information collected to test the null hypothesis. iii. If we do not reject the null hypothesis based on sample evidence, we have proven beyond doubt that the null hypothesis is true. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

757)

i. If we do not reject the null hypothesis based on sample evidence, we have proven beyond doubt that the null hypothesis is true. ii. A test statistic is a value determined from sample information collected to test the null hypothesis. iii. The region or area of rejection defines the location of all those values that are so large or so small that the probability of their occurrence under a true null hypothesis is rather remote. A) (ii) and (iii) are correct statements but not (i). B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

758)

i. To set up a decision rule, the sampling distribution is divided into two regions-a region of non-rejection and a region where the null hypothesis is rejected. ii. A test statistic is a value determined from sample information collected to test the null hypothesis. iii. If the null hypothesis is true and the researchers do not reject it, then a correct decision has been made. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

759)

It is claimed that in a bushel of peaches less than ten percent are defective. A sample of 400 peaches is examined and 50 are found to be defective.

759.1) If α = 0.025, what will be the decision? A) Fail to reject the null and conclude the defects are not greater than 10% B) Reject the null and conclude the defects are not greater than 10% C) Reject the null and conclude the defects are greater than 10% D) Fail to reject the null and conclude the defects are not less than 10%

759.2) What is the alternate hypothesis for a one-sided test? A) p ≠ 0.10 B) p > 0.10 C) p ≤ 0.10 D) p = 0.10 E) p < 0.10

759.3) What is the null hypothesis? A) p ≠ 0.10 B) p ≥ 0.10 C) p ≤ 0.10 D) p < 0.10 E) p = 0.10

759.4) What is the critical value for α = 0.025? A) 1.96 B) ±1.65 C) -1.96 D) -1.65

759.5) What is the sample proportion? A) 0.10 B) 0.125 C) 40 D) 0.40

759.6) What is the z-statistic? A) 0.025 B) 0.278 C) -1.65 D) 1.67

760)

i. The fifth and final step in testing a hypothesis is taking a sample and, based on the decision rule, deciding if the null hypothesis should be rejected. ii. When the null hypothesis is not rejected, the conclusion is that our sample data does not allow us to reject the null hypothesis. iii. The level of significance is selected after setting up a decision rule and sampling the population. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

761)

i. To prevent bias, the level of significance is selected before setting up the decision rule and sampling the population. ii. The fifth and final step in testing a hypothesis is taking a sample and, based on the decision rule, deciding if the null hypothesis should be rejected. iii. When the null hypothesis is not rejected, the conclusion is that our sample data does not allow us to reject the null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

762)

i. The first step in testing a hypothesis is to state the decision rule. ii. To prevent bias, the level of significance is selected before setting up the decision rule and sampling the population. iii. The fifth and final step in testing a hypothesis is taking a sample and, based on the decision rule, deciding if the null hypothesis should be rejected. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

763)

i. To prevent bias, the level of significance is selected before setting up the decision rule and sampling the population. ii. The level of significance is the probability that a true hypothesis is rejected. iii. If the critical values of the test statistic z are ±1.96, they are the dividing points between the areas of rejection and non-rejection. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (ii) and (iii) are correct statements but not (i).

764)

765)

The null hypothesis makes a claim about what value? A) Population parameter B) Sample statistic C) Sample mean D) Type II error

The average cost of tuition, room and board at community colleges is reported to be $11,500 per year but a financial administrator believes that the average cost is higher. A study conducted using 150 community colleges showed that the average cost per year is $12,000 with a standard deviation of $1,200. Let α = 0.05.

765.1) What are the null and alternative hypotheses for this study? A) Null: μ ≤ $12,000; alternative: μ > $12,000 B) Null: μ ≤ $12,000; alternative: μ < $12,000 C) Null: μ ≤ $11,500; alternative: μ > $11,500 D) Null: μ ≤ $11,500; alternative: μ < $11,500

765.2) If using Z, what is the critical z-value for this test? A) + 1.96 B) -1.96 C) + 1.65 D) -1.65

765.3) Given the z-statistic is 5.1, what is our decision about the average cost? A) Equal to $11,500 B) Greater than $11,500 C) Less than $11,500 D) Not equal to $11,500

766)

What do we call the statement that determines if the null hypothesis is rejected? A) Decision rule B) Test statistic C) Alternate hypothesis D) Critical value

767)

Which of the following is NOT one of the five steps in the hypothesis testing procedure? A) Formulate a decision rule B) State the null and alternate hypotheses C) Select a level for β D) Identify the test statistic

If the alternate hypothesis states that μ does not equal 4,000, what is the rejection region for the hypothesis test? A) Both tails B) Lower or left tail C) Upper or right tail D) Center

768)

769)

What are the two rejection areas in using a two-tailed test and the 0.01 level of significance when the population standard deviation is known? A) Above 1.96 and below -1.96 B) Above 1.65 and below -1.65 C) Above 2.58 and below -2.58 D) Above 1.00 and below -1.00

770)

What are the critical z-values for a two-tailed hypothesis test if α = 0.01? A) ±1.96 B) ±2.33 C) ±2.58 D) ±1.65

i. If the null hypothesis is μ≥ 200 and the alternate hypothesis states that μ is less than 200, then, a two-tail test is being conducted. ii. For a one-tailed test of hypothesis, the area of rejection is only in one tail of the curve. iii. As the sample size increases, the curve of the t-distribution approaches the standard normal distribution A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

771)

If the alternative hypothesis states that μ > 6,700, what is the rejection region for the hypothesis test? A) Both tails B) Lower tail C) Upper tail D) Center

772)

773)

The mean gross annual incomes of certified tack welders are normally distributed with the mean of $50,000 and a standard deviation of $4,000. The ship building association wishes to find out whether their tack welders earn more or less than $50,000 annually. The alternate hypothesis is that the mean is not $50,000.

773.1) Which of the following is the alternate hypothesis? A) p ≠ $50,000 B) μ ≠ $50,000 C) μ < $50,000 D) μ = $50,000 E) p = $50,000

773.2) If the level of significance is 0.10, what is the decision rule? A) Do not reject the null hypothesis if computed z lies between -1.65 and + 1.65;

otherwise, reject it. B) Do not reject the null hypothesis if computed z is greater than 1.65; otherwise, reject it. C) Do not reject the null hypothesis if computed z lies between -1.96 and + 1.96; otherwise, reject it. D) Reject the null hypothesis if computed z is below -1.96; otherwise, reject it.

773.3) If the level of significance is 0.10, what is the critical value? A) 1.65 B) 2.58 C) 1.28 D) ±1.28 E) ±1.645

773.4) Given the following MegaStat printout, what conclusions can be made? Hypothesis Test: Mean vs. Hypothesized Value 50,000.00

hypothesized value

55,500.00

mean 50000

4,000.00

std. dev.

707.11

std. error

7.78

7.33E-15

p-value(two-tailed)

53,678.61

confidence interval 99% lower

57,321.39

confidence interval 99% upper

A) There is a 1.68% chance of getting these sample results if the annual income is

actually $50,000. B) Since the p-value is 7%, we reject the null hypothesis at a 5% level of significance. C) Since the p-value is 9%, we have insufficient evidence to reject the null hypothesis at the 5% level of significance. D) Since the p-value is 9%, we reject the null hypothesis at the 1% level of significance. E) Since the p-value is incredibly small (far less than 1%), we reject the null hypothesis at the 1% level of significance.

773.5) When tested at the 99% level, these are the results found with MegaStat: Hypothesis Test: Mean vs. Hypothesized Value 50,000.00

hypothesized value

50,555.00

mean income

4,000.00

std. dev.

707.11

std. error

0.78

.4325

p-value(two-tailed)

A) Since the p-value is 0.43 at this level of testing, there is insufficient evidence to say

that the welders earn an income different from $50,000. B) Since the p-value is 0.43 at this level of testing, there is sufficient evidence to say that the welders earn more than $50,000. C) The p-value of 0.043 indicates that there is sufficient evidence to say that the welders earn more than $50,000.

774)

A restaurant that bills its house account monthly is concerned that the average monthly bill exceeds $200 per account. A random sample of twelve accounts is selected, resulting in a sample mean of $220 and a standard deviation of $12.

774.1) The t-test is to be conducted at the 5% level of significance. A) The null hypothesis is μ ≤ 200. The alternate hypothesis is μ ≤ 200. B) The null hypothesis is μ ≤ 200. The alternate hypothesis is μ > 200. C) The null hypothesis is μ = 200. The alternate hypothesis is μ ≠ 200. D) The null hypothesis is μ > 200. The alternate hypothesis is μ ≤ 200 E) The null hypothesis is μ ≤ 220. The alternate hypothesis is μ > 220.

774.2) The t-test is to be conducted at the 5% level of significance. A) The critical value of t is + 1.796. The calculated value of t is + 5.77. B) The critical value of t is -1.796. The calculated value of t is negative 5.77. C) The critical value of t is + 2.201. The calculated value of t is + 5.77. D) The critical value of t is + 2.201. The calculated value of t is + 1.40. E) The critical value of t is + 2.201. The calculated value of t is -5.77.

774.3) The t-test is to be conducted at the 5% level of significance.

The t-value is calculated to be 5.77. At the 0.01 level of significance, what is your decision? A) You reject the null hypothesis, and agree that the average monthly bill exceeds $200. B) You have insufficient evidence to reject the null hypothesis. C) You reject the alternate hypothesis and agree that the average monthly bill is less than $200. D) You should have used the z-test.

775)

A nationwide survey of college students was conducted and found that students spend two hours per class for studying. A professor at your school wants to determine whether the time students spend at your school is significantly different from the two hours.

775.1) A random sample of fifteen statistics students is carried out and the findings indicate an

average of 1.75 hours with a standard deviation of 0.24 hours. A) H0 is μ ≠ 2. H1 is μ = 2. B) H0 is μ = 2. H1 is μ ≠ 2. C) H0 is μ = 2. H1 is μ > 2. D) H0 is μ = 2. H1 is μ < 2. E) H0 is μ ≠ 2. H1 is μ > 2.

775.2) A random sample of fifteen statistics students is carried out and the findings indicate an

average of 1.75 hours with a standard deviation of 0.24 hours. Test at the 5% level of significance. A) The critical value of t is -4.03. The calculated value of t is ±2.145. B) The critical value of t is ±2.145. The calculated value of t is -4.03. C) The critical value of t is 1.761. The calculated value of t is -4.03. D) The critical value of t is ±1.761. The calculated value of t is -1.041. E) The t-test should not be used. Rather, use the z-test.

775.3) A random sample of fifteen statistics students is carried out and the findings indicate an

average of 1.75 hours with a standard deviation of 0.24 hours. Given the following printout, what can you determine? Hypothesis Test: Mean vs. Hypothesized Value 2.0

hypothesized value

1.75

mean study hours

0.24

std. dev.

0.578

std. error

-0.43

.6721

p-value (two-tailed)

A) The alternate hypothesis is μ ≤ 2 B) You should accept the null hypothesis at the 0.05 level of significance. C) There is less than a 1% chance of getting these results if the null hypothesis is true, so

you have very strong evidence to suggest that the average number of study hours is different from 2. D) You should reject the null hypothesis at the 0.05 level of significance, but accept it when testing at the 0.01 level of significance. E) You should fail to reject the null hypothesis and conclude the number of study hours is not different from 2.

776)

A random sample of size 15 is selected from a normal population. The population standard deviation is unknown. Assume that a two-tailed test at the 0.10 significance level is to be used. For what value of t will the null hypothesis be rejected? A) To the left of -1.282 or to the right of 1.282 B) To the left of -1.345 or to the right of 1.345 C) To the left of -1.761 or to the right of 1.761 D) To the left of -1.645 or to the right of 1.645

777)

What is the critical value for a right-tailed hypothesis test in which a null hypothesis is tested at the 5% level of significance based on a sample size of 25 and an unknown population standard deviation? A) 1.708 B) 1.711 C) 2.060 D) 2.064

778)

Records on a fleet of trucks reveal that the average life of a set of spark plugs is normally distributed with a mean of 35,600 kilometres. A manufacturer of spark plugs claims that its plugs have an average life in excess of 35,600 kilometres. The fleet owner purchased 18 sets and found that the sample average life was 37,700 kilometres, the sample standard deviation was 2415 kilometres and the computed t = 3.677. A) Based on these findings, there is enough evidence to accept the manufacturer's claim at the 0.05 level. B) Based on these findings, there is NOT enough evidence to accept the manufacturer's claim at the 0.05 level. C) Based on these findings, there is enough evidence to accept the manufacturer's claim at the 0.05 level, but NOT at the 0.01 level. D) Based on these findings, there is NOT enough evidence to accept the manufacturer's claim at the 0.01 level. E) Based on these findings, there in NOT enough evidence to accept the manufacturer's claim at either the 0.05 or the 0.01 level.

779)

i. For a one-tailed test using the 0.05 level of significance, the critical value for the z test is 1.645, but for t it is 1.96. ii. For a one-tailed test using the 0.01 level of significance, the critical value for the z-test is 1.645, but for t it is 1.96. iii. For a two-tailed test using the 0.05 level of significance the critical value for the z-test is 1.96 and it is the same for the t-test. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

780)

The mean length of a small counter balance bar is 43 millimeters. There is concern that the adjustments of the machine producing the bars have changed. Test the claim at the 0.02 level that there has been no change in the mean length. The alternate hypothesis is that there has been a change. Twelve bars ( n = 12) were selected at random and their lengths recorded. The lengths are (in millimeters) 42, 39, 42, 45, 43, 40, 39, 41, 40, 42, 43 and 42. The mean of the sample is 41.5 and the standard deviation 1.784. Computed t = -2.913. Has there been a statistically significant change in the mean length of the bars? A) Yes, because the computed t lies in the area beyond the critical. B) No, because the information given is not complete. C) No, because the computed t lies in the area to the right of -2.718.

781)

From past records it is known that the average life of a battery used in a digital clock is 305 days. The battery life is normally distributed. The battery was recently modified to last longer. A sample of 20 of the modified batteries was tested. It was discovered that the mean life was 311 days and the sample standard deviation was 12 days. We want to test at the 0.05 level of significance whether the modification increases the life of the battery. What is our decision rule? A) Do not reject the null hypothesis if computed t is 1.96 or greater B) Reject the null hypothesis if computed t is less than 1.96 C) Do not reject the null hypothesis if computed t is 1.729 or greater D) Reject the null hypothesis if computed t is 2.086 or greater E) Reject the null hypothesis if the computed t is 1.729 or greater

782)

A manufacturer wants to increase the shelf life of a line of cake mixes. Past records indicate that the average shelf life of the mix is 216 days. After a revised mix has been developed, a sample of nine boxes of cake mix gave these shelf lives (in days): 215, 217, 218, 219, 216, 217, 217, 218 and 218. At the 0.025 level, has the shelf life of the cake mix increased? A) Yes, because computed t is greater than the critical value. B) Yes, because computed t is less than the critical value. C) No, because computed t lies in the region of acceptance. D) No, because 217.24 is quite close to 216.

783)

A manufacturer wants to increase the absorption capacity of a sponge. Based on past data, the average sponge could absorb 103.5ml. After the redesign, the absorption amounts of a sample of sponges were (in millilitres): 121.3, 109.2, 97.6, 103.5, 112.4, 115.3, 106.5, 112.4, 118.3, and 115.3. What is the decision rule at the 0.01 level of significance to test if the new design increased the absorption amount of the sponge? A) Do not reject null hypothesis if computed t is less than 2.580 B) Do not reject null hypothesis if computed t is less than 2.821 C) Reject null hypothesis if computed z is 1.96 or larger D) Reject null hypothesis if computed t is less than 2.764

784)

A machine is set to fill the small size packages of Smarties candies with 56 candies per bag. A sample revealed: 3 bags of 56, 2 bags of 57, 1 bag of 55, and 2 bags of 58. How many degrees of freedom are there? A) 9 B) 1 C) 8 D) 7

785)

What is the critical value for t in a one-tailed hypothesis test in which a null hypothesis is tested at the 5% level of significance based on a sample size of 15? A) 1.708 B) 1.711 C) 1.761 D) 2.145

786)

To conduct a test of hypothesis with a small sample, we need to be able to make the following assumption that: A) a larger computed value of t will be needed to reject the null hypothesis. B) the region of acceptance will be wider than for large samples. C) the confidence interval will be wider than for large samples. D) the population is normally distributed.

787)

If the 1% level of significance is used and the computed value of z is + 6.00, what is our decision? A) Do not reject H0 B) Reject H0 C) Reject H1

788)

For a two-tailed test at the 0.05 significance level, what is the rejection region when the population standard deviation is known? A) Between ±1.96 B) Between ±1.65 C) Greater than + 1.96 and less than -1.96 D) Greater than + 1.65 and less than -1.65

789)

What is the critical z-value for a one-tailed lower test at the 1% level of risk? A) + 2.58 B) -2.58 C) + 2.33 D) -2.33

790)

Which of the following is a test statistic used to test a hypothesis about a population? A) α B) β C) μ D) z

791)

If α = 0.05 for a two-tailed test, how large is the acceptance area? A) 0.050 B) 0.025 C) 0.950 D) 0.975

792)

For a one-tailed hypothesis test, the critical z-value of the test statistic is -2.33. Which of the following is true about the hypothesis test? A) α = 0.05 for a lower-tailed test B) α = 0.01 for a lower-tailed test C) α = 0.05 for an upper-tailed test D) α = 0.01 for an upper-tailed test

793)

A manufacturer claims that less than 1% of all his products do not meet the minimum government standards. A survey of 500 products revealed ten did not meet the standard.

793.1) If the z-statistic is 2.25 and the level of significance is 0.02, what is your decision? A) You reject the null hypothesis and agree that less than 1% fail to meet government

standards. B) You have insufficient evidence to reject the null hypothesis. Conclude that ≥ 1% of his products fail to meet the standard. C) You reject the alternate hypothesis and agree that less than 1% meet government standards. D) You should have used the t-test.

793.2) If the z-statistic is -2.054 and the level of significance is 0.03, what is your decision? A) You reject the null hypothesis, and agree that less than 1% fail to meet government

standards. B) You have insufficient evidence to reject the null hypothesis. C) You reject the alternate hypothesis and agree that less than 1% meet government standards. D) You should have used the t-test.

793.3) If the computed value of z = -2.25 and the level of significance is 0.03, what is your

decision? A) You reject the null hypothesis, and agree that less than 1% fail to meet government standards. B) You have insufficient evidence to reject the null hypothesis. C) You reject the alternate hypothesis and agree that less than 1% meet government standards. D) You should have used the t-test.

794)

A manufacturer of stereo equipment introduces new models in the fall. Retail dealers are surveyed immediately after the Christmas selling season regarding their stock on hand of each piece of equipment. It has been discovered that unless 40% of the new equipment ordered by the retailers in the fall had been sold by Christmas, immediate production cutbacks are needed. The manufacturer has found that contacting all of the dealers after Christmas by mail is frustrating as many of them never respond. This year 80 dealers were selected at random and telephoned regarding a new receiver. It was discovered that 38% of those receivers had been sold. Since 38% is less than 40%, does this mean that immediate production cutbacks are needed or can this difference of 2 percentage points be attributed to sampling? Test at the 0.05 level. Computed z = -0.37. A) Cut back production B) Do not cut back production C) Cannot determine based on information given

795)

What does z equal for an α = 0.01 and a left tailed test? A) + 2.33 B) -2.33 C) + 2.58 D) -2.58

796)

The following summarizes the average of the Composite Index at the end of 20 randomly selected weeks in 2021. Hypothesis Test: Mean vs. Hypothesized Value 9,600.00000

hypothesized value

9,776.12600

mean Composite intex

659.28752

std. dev.

147.42117

std. error

1.19

.1235

p-value(one-tailed, upper)

9,467.56985

confidence interval 95%lower

10,084.68215

confidence interval 95% upper

308.55615

half-width

Using a 5% level of significance, can it be agreed that the Index average was more than $9,600 during the year 2021? A) Fail to reject the null hypothesis and conclude the mean index was 9,600. B) Reject the null hypothesis and conclude the mean index was lower than 9,600. C) Reject the null hypothesis and conclude the mean index was greater than 9,600. D) Reject the null hypothesis and conclude the mean index was different from 9,600.

797)

The printout below refers to the weekly closing stock prices for SafeFare on 20 randomly selected weeks in 2021. Hypothesis Test: Mean vs. Hypothesized Value 19.50000

hypothesized value

17.38750

mean SafeFare

2.48368

std. dev.

0.55537

std. error

-3.80

.0012

p-value(two-tailed)

16.22510

confidence interval 95% lower

18.54990

confidence interval 95% upper

1.16240

half-width

Using a 5% level of significance, can you say that the average SafeFare stock price was different from $19.50? A) Fail to reject the null hypothesis and conclude the mean stock price was $19.50. B) Reject the null hypothesis and conclude the mean stock price was lower than $19.50. C) Reject the null hypothesis and conclude the mean index was greater than $19.50. D) Reject the null hypothesis and conclude the mean index was different from $19.50.

798)

One of the major U.S. tire makers wishes to review its warranty for their rainmaker tire. The warranty is for 40,000 miles. The tire company believes that the tire actually lasts more than 40,000 miles with a standard deviation of 15,000 miles.

798.1) A sample 49 tires revealed that the mean number of miles is 45,000 miles. Test the

hypothesis with a 0.05 significance level. A) H0 is μ ≥ 40,000 H1 is μ > 40,000 B) H0 is μ = 40,000 H1 is μ > 40,000 C) H0 is μ ≤ 40,000 H1 is μ = 40,000 D) H0 is μ = 40,000 H1 is μ ≠ 40,000

798.2) A sample 49 tires revealed that the mean number of miles is 45,000 miles. Test the

hypothesis with a 0.05 significance level. A) The decision rule is to reject if Z > 1.645. The calculated value of z is + 2.33. B) The decision rule is to reject if Z < 1.645. The calculated value of z is -2.33. C) The decision rule is to reject if Z > 1.96. The calculated value of z is + 2.33. D) The decision rule is to reject if Z < 1.96. The calculated value of z is + 2.33.

798.3) A sample 49 tires revealed that the mean number of miles is 45,000 miles. Test the

hypothesis with a 0.05 significance level. A) At a 5% level of significance, our decision is to reject the null hypothesis. The tires last more than 40 000 miles. B) At a 5% level of significance, our decision is to accept the null hypothesis. The tires last 40,000 miles. C) At a 5% level of significance, we should have used the t-test, rather than the z-test.

799)

The mean weight of newborn infants at a community hospital is said to be 6.6 pounds. A sample of seven infants is randomly selected and their weights at birth are recorded as 9.0, 7.3, 6.0, 8.8, 6.8, 8.4, and 6.6 pounds.

799.1) Does this sample support the original claim? The null hypothesis is: A) μ = 6.6 B) μ ≠ 6.6 C) μ ≥ 6.6 D) μ > 7.6 E) μ ≠ 7.6

799.2) pounds. Does this sample support the original claim? What is the alternate hypothesis? A) μ = 6.6 B) μ ≠ 6.6 C) μ ≥ 6.6 D) μ > 7.6 E) μ ≠ 7.6

799.3) What are the degrees of freedom associated with this claim? A) 7 B) 8 C) 6 D) 6.6 E) 7.6

799.4) If α = 0.05, what is the critical t value? A) -2.365 B) ±1.96 C) ±2.365 D) ±2.447 E) -2.447

799.5) What is the sample mean? A) 6.6 B) 7.6 C) 1.177 D) 2.447

799.6) What is the sample variance? A) 1.188 B) 6.6 C) 1.386 D) 7.6

799.7) What is the sample standard deviation? A) 1.177 B) 6.6 C) 1.090 D) 7.6

799.8) Does this sample support the original claim?

What is the decision for a statistical significant change in average weights at birth at the 5% level of significance? Hypothesis Test: Mean vs. Hypothesized Value

A) B) C) D)

6.6000

hypothesized value

7.5571

mean Data

1.1774

std. dev.

0.4450

std. error

2.15

.0750

p-value(two-tailed)

Fail to reject the null hypothesis and conclude the mean is 6.6 lb. Reject the null hypothesis and conclude the mean is higher than 6.6 lb. Reject the null hypothesis and conclude the mean is lower than 6.6 lb. Cannot calculate because population standard deviation is unknown.

799.9) Does this sample support the original claim? What is the decision for a significant

increase in the average birthrate at a 5% level of significance? Hypothesis Test: Mean vs. Hypothesized Value

A) B) C) D)

6.6000

hypothesized value

7.5571

mean Data

1.1774

std. dev.

0.4450

std. error

2.151

.0375

p-value(one-tailed, upper)

6.4683

confidence interval 95% lower

8.6460

confidence interval 95% upper

Fail to reject the null hypothesis and conclude the mean is 6.6 lb. Reject the null hypothesis and conclude the mean is lower than 6.6 lb. Reject the null hypothesis and conclude the mean is greater than 6.6 lb. Cannot calculate because population standard deviation is unknown.

800)

The dean of a business school claims that the average starting salary of its graduates is more than $50,000. It is known that the population standard deviation is $10,000.

800.1) Sample data on the starting salaries of 36 randomly selected recent graduates yielded a

mean of $62,000. What is the value of the sample test statistic? A) z = 7.2 B) t = 5.04 C) z = 2.7 D) z = 5.6

800.2) Sample data on the starting salaries of 36 randomly selected recent graduates yielded a

mean of $52,000. What is the value of the sample test statistic? A) z = 1.2 B) t = 7.2 C) t = 0.12 D) t = 1.22

800.3) Sample data on the starting salaries of 25 randomly selected recent graduates yielded a

mean of $52,000. What is the value of the sample test statistic? A) z = 1.0 B) t = 7.2 C) t = 5.04 D) t = 1.22

800.4) Sample data on the starting salaries of 20 randomly selected recent graduates yielded a

mean of $55,000. What is the value of the sample test statistic? A) z = 2.24 B) t = 7.2 C) t = 5.04 D) t = 2.24

801)

Given: Null hypothesis is that the population mean is 16.9 against the alternative hypothesis that the population mean is not equal to 16.9.

801.1) A random sample of 16 items results in a sample mean of 17.1 and the sample standard

deviation is 2.4. It can be assumed that the population is normally distributed. Determine the observed " t" value. A) t = 2.12 B) t = 1.33 C) t = 1.753 D) t = 0.33

801.2) A random sample of 16 items results in a sample mean of 17.8 and the sample standard

deviation is 2.4. It can be assumed that the population is normally distributed. Determine the observed " t" value. A) t = 2.12 B) t = 1.50 C) t = 1.75 D) t = 1.00

801.3) A random sample of 16 items results in a sample mean of 18.0 and the sample standard

deviation is 2.4. It can be assumed that the population is normally distributed. Determine the observed "t" value. A) t = 2.12 B) t = 1.50 C) t = 1.75 D) t = 1.83

801.4) A random sample of 25 items results in a sample mean of 18.0 and the sample standard

deviation is 2.4. It can be assumed that the population is normally distributed. Determine the observed "t" value. A) t = 2.29 B) t = 1.83 C) t = 1.75 D) t = 2.01

801.5) A random sample of 25 items results in a sample mean of 17.1 and the sample standard

deviation is 2.4. It can be assumed that the population is normally distributed. Determine the observed "t" value. A) t = 0.83 B) t = 1.83 C) t = 1.75 D) t = 0.42

801.6) A random sample of 25 items results in a sample mean of 17.8 and the sample standard

deviation is 2.4. It can be assumed that the population is normally distributed. Determine the observed "t" value. A) t = 1.88 B) t = 1.83 C) t = 1.75 D) t = 2.21

802)

The sample size and the population proportion are respectively represented by what symbols? A) p and n B) α and β C) z and t D) n and p

803)

Test at the 0.01 level the statement that 55% of those families who plan to purchase a vacation residence in Florida want a condominium. The null hypothesis is p = 0.55 and the alternate is p ≠ 0.55. A random sample of 400 families who planned to buy a vacation residence revealed that 228 families want a condominium. What decision should be made regarding the null hypothesis? A) Do not reject it B) Reject it C) Cannot accept nor reject it based on the information given

804)

If 20 out of 50 students sampled live in a college dormitory, what is the estimated proportion of students at the University living in a dormitory? A) 0.20 B) 0.40 C) 0.50 D) 0.60

805)

What must both np and n(1 - p) exceed in testing a hypothesis involving one proportion? A) 5 B) 30 C) 100 D) 2,000

806)

What do tests of proportions require of both np and n(1 - p)? A) Exceed 30 B) Exceed 5 C) Exceed 100 D) Be equal

807)

The claim that "40% of those persons who retired from an industrial job before the age of 60 would return to work if a suitable job was available" is to be investigated at the 0.02 level of risk. If 74 out of the 200 workers sampled said they would return to work, what is our decision? A) Do no reject the null hypothesis because -0.866 lies in the region between 0 and -2.33 B) Do not reject the null hypothesis because -0.866 lies in the region between 0 and 2.58 C) Reject the null hypothesis because 37% is less than 40% D) Do not reject the null hypothesis because 37% lies in the area between 0% and 40%

808)

i. One assumption in testing a hypothesis about a proportion is that the data collected are the result of counting something. ii. One assumption in testing a hypothesis about a proportion is that an outcome of an experiment can be classified into two mutually exclusive categories, namely, a success or a failure. iii. A proportion is a fraction, ratio or probability that gives the part of the population or sample that has a particular trait of interest. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

809)

i. A sample proportion is found by dividing the number of successes in the sample by the number sampled. ii. The standard normal distribution is the appropriate distribution when testing a hypothesis about a population proportion. iii. When testing population proportions, the z statistic can be used when np and n(1 - p) are greater than five. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

810)

i. A sample proportion is found by dividing the number of successes in the sample by the number sampled. ii. The standard normal distribution is the appropriate distribution when testing a hypothesis about a population proportion. iii. To conduct a test of proportions, the assumptions required for the binomial distribution must be met. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

811)

i. The standard normal distribution is the appropriate distribution when testing a hypothesis about a population proportion. ii. When testing population proportions, the z statistic can be used when np and n(1 - p) are greater than five. iii. To conduct a test of proportions, the assumptions required for the binomial distribution must be met. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

812)

Based on the Nielsen ratings, the local CBS affiliate claims its 11:00 PM newscast reaches 41% of the viewing audience in the area. In a survey of 100 viewers, 36% indicated that they watch the late evening news on this local CBS station.

812.1) What is the null hypothesis? A) p = 0.36 B) p = 0.41 C) p ≠ 0.36 D) μ = 0.41

812.2) What is the alternate hypothesis? A) p = 0.36 B) p = 0.41 C) p ≠ 0.41 D) μ ≠ 0.41

812.3) What is the sample proportion? A) 0.41 B) 0.36% C) 0.41% D) 0.36

812.4) What is the critical value if α = 0.01? A) 2.58 B) 2.33 C) ±2.58 D) -2.33

812.5) What is the z-statistic? A) 1.02 B) 1.22 C) -1.02 D) -1.22

812.6) What is the critical value if the level of significance is 0.10? A) -1.282 B) ±1.65 C) -2.58 D) 2.58

812.7) What is your decision if α = 0.01? A) Fail to reject the null hypothesis and conclude about 41%. B) Reject the null hypothesis and conclude different from 41%. C) Fail to reject the alternate and conclude different from 41%. D) Reject the alternate and conclude it is 41%.

813)

A manufacturer claims that less than 1% of all his products do not meet the minimum government standards. A survey of 500 products revealed ten did not meet the standard. A) The null hypothesis is p ≥ 0.01. The alternate hypothesis is p < 0.01 B) The null hypothesis is p = 0.01. The alternate hypothesis is p > 0.01 C) The null hypothesis is p ≥ 0.01. The alternate hypothesis is p > 0.01 D) The null hypothesis is p = 0.01. The alternate hypothesis is p ≠ 0.01 E) The null hypothesis is p < 0.01. The alternate hypothesis is p ≠ 0.01

814)

A manufacturer claims that less than 1% of all his products do not meet the minimum government standards. A survey of 500 products revealed ten did not meet the standard. A) If α =.01, the critical value is z = -2.33 B) If α =.01, the critical value is z = 2.33 C) If α =.01, the critical value is z = -1.96 D) If α =.01, the critical value is z = 1.96 E) If α =.01, the critical value is z = -2.58

815)

A manufacturer claims that less than 1% of all his products do not meet the minimum government standards. A survey of 500 products revealed ten did not meet the standard. A) The z-statistic is -2.25 B) The z-statistic is 2.25 C) The z-statistic is -1.00 D) The z-statistic is 1.00

816)

A manufacturer claims that less than 1% of all his products do not meet the minimum government standards. A survey of 500 products revealed ten did not meet the standard. If the level of significance is 2%, what is the critical value? A) 2.05 B) -2.05 C) 2.33 D) -2.33 E) 1.96

817)

A manufacturer claims that less than 1% of all his products do not meet the minimum government standards. A survey of 500 products revealed ten did not meet the standard. If the z-statistic is -1.96 and the level of significance is 0.01, what is your decision? A) You reject the null hypothesis. B) You have insufficient evidence to reject the null hypothesis. C) You accept the alternate hypothesis and agree that less than 1% meet government standards. D) You should have used the t-test.

818)

If α = 0.05, what is the probability of making a Type I error? A) 0 B) 1/20 C) 19/20 D) 20/20

819)

i. The probability of a Type I error is also referred to as alpha. ii. A Type I error is the probability of accepting a true null hypothesis. iii. A Type I error is the probability of rejecting a true null hypothesis. A) (i), (ii) and (iii) are all correct statements. B) (i) is a correct statement but not (ii) and (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

i. If the critical values of the test statistic z are ±1.96, they are the dividing points between the areas of rejection and non-rejection. ii. The probability of a Type I error is also referred to as alpha. iii. A Type I error is the probability of accepting a true null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

820)

i. If the critical values of the test statistic z are ±1.96, they are the dividing points between the areas of rejection and non-rejection. ii. The probability of a Type I error is also referred to as alpha. iii. A Type I error is the probability of rejecting a true null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

821)

822)

What is a Type II error? A) Accepting a false null hypothesis B) Rejecting a false null hypothesis C) Accepting a false alternate hypothesis D) Rejecting a false alternate hypothesis

823)

What is the probability of making a Type II error if the null hypothesis is actually true? A) α B) 1 C) 0 D) 0.05

824)

What is the level of significance? A) Probability of a Type II error B) Probability of a Type I error C) z-value of 1.96 D) Beta error

825)

The average cost of tuition, room and board at community colleges is reported to be $8,500 per year, but a financial administrator believes that the average cost is higher. A study conducted using 150 community colleges showed that the average cost per year is $9,000 with a standard deviation of $1,200. Let α = 0.05. Given the following MegaStat printout, explain the meaning of the p-value. Hypothesis Test: Mean vs. Hypothesized Value 8,500.00

hypothesized value

9,000.00

mean college cost

1,200.00

std. dev.

97.98

std. error

150

5.10

1.67E-07

p-value (one-tailed, upper)

A) There is a 1.67% chance of getting these sample results if the null hypothesis is true. B) There is a 16.7% chance of getting these sample results if the null hypothesis is true. C) There is an incredibly small chance of getting these sample results if the null

hypothesis is true; therefore we have strong evidence to support that college costs are more than $8,500. D) There is an incredibly large chance of getting these sample results if the null hypothesis is true; therefore we are unable to reject the claim that college costs are $8,500.

826)

The printout below refers to the weekly closing stock prices for FreshAir on 20 randomly selected weeks in 2020. Hypothesis Test: Mean vs. Hypothesized Value 19.50000

hypothesized value

17.38750

mean FreshAir

2.48368

std. dev.

0.55537

std. error

-3.80

.0006

p-value (one-tailed, lower)

826.1) Using a 5% level of significance, can you say that the average FreshAir stock price was

less than $19.50? A) Fail to reject the null hypothesis and conclude the mean stock price was $19.50. B) Since the P-value is less than the selected alpha, reject the null hypothesis and conclude the mean stock price was lower than $19.50. C) Since the P-value is more than the selected alpha, reject the null hypothesis and conclude the mean stock price was less than $19.50. D) Since the P-value is less than the selected alpha, reject the null hypothesis and conclude the mean stock price was different from $19.50.

826.2) Using a 2% level of significance, can you say that the average FreshAir stock price was

826.3) Using a 1% level of significance, can you say that the average FreshAir stock price was

827)

A restaurant that bills its house account monthly is concerned that the average monthly bill exceeds $200 per account. A random sample of twelve accounts are selected, resulting in a sample mean of $220 and a standard deviation of $12. The t-test is to be conducted at the 5% level of significance. Given the following printout, what can you determine? Hypothesis Test: Mean vs. Hypothesized Value .00

hypothesized value

.00

mean accounts

.00

std. dev.

.46

std. error N Df

.77

.0001

p-value (one-tailed, lower)

A) The alternate hypothesis is μ ≤ 200 B) You should accept the null hypothesis at the 0.05 level of significance. C) There is less than a 1% chance of getting these results if the null hypothesis is true, so

you have very strong evidence to suggest that the average bill is more than $200. D) There is less than a 1% chance of getting these results if the null hypothesis is true, so you have very strong evidence to suggest that the average bill is less than $200. E) The alternate hypothesis is μ ≤ 200 and you should accept the null hypothesis at the 0.05 level of significance.

828)

The Jamestown Steel Company manufactures and assembles desks and other office equipment at several plants. The weekly production of the Model A325 desk follows a normal probability distribution, with a mean of 200 and a standard deviation of 16. Recently, due to market expansion, new production methods have been introduced and new employees are hired. The vice president of manufacturing company would like to investigate whether there has been a change in the weekly production of the Model A325 desk. The mean number of desks produced last year (50 weeks, because the plant was shut down two weeks for vacation) is 203.5.

828.1) Is the mean number of desks produced different from 200? Test using the.01 significance

level. A) The alternate hypothesis is μ ≤ 200. B) It is appropriate to use the z-test. C) The decision rule is: if the computed value of the test statistic is not between -1.645

and 1.645, reject the null hypothesis. D) The area where H0 is not rejected is therefore.98.

828.2) Is the mean number of desks produced different from 200? Test using the.01 significance

level. i. The alternate hypothesis is μ ≤ 200. ii. It is appropriate to use the z-test. iii. The decision rule is: if the computed value of the test statistic is not between -2.58 and 2.58, reject the null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

828.3) Is the mean number of desks produced different from 200? Test using the.01 significance

level. i. The alternate hypothesis is μ ≠ 200. ii. It is appropriate to use the z-test. iii. The decision rule is: if the computed value of the test statistic is not between -2.58 and 2.58, reject the null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

828.4) Is the mean number of desks produced different from 200? Test using the.01 significance

level. i. The alternate hypothesis is μ ≠ 200. ii. The calculated value of z is 1.55. iii. The decision rule is: if the computed value of the test statistic is not between -2.58 and 2.58, reject the null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

828.5) Is the mean number of desks produced different from 200? Test using the.01 significance

level. i. The alternate hypothesis is μ ≠ 200. ii. The calculated value of z is 2.55. iii. The decision rule is: if the computed value of the test statistic is not between -2.58 and 2.58, reject the null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

828.6) Is the mean number of desks increased from 200? Test using the.01 significance level. Hypothesis Test: Mean vs. Hypothesized Value 200.000

hypothesized value

203.500

mean production

16.000

std. dev.

2.263

std. error

1.55

.0610

p-value(one-tailed, lower)

197.672

confidence interval 99% lower

209.328

confidence interval 99% upper

5.828

half-width

A) Reject the null hypothesis; there is sufficient evidence to indicate an increase in the

weekly production. B) Unable to reject the null hypothesis; there is sufficient evidence to indicate a change in weekly production. C) Unable to reject the null hypothesis; there is insufficient evidence to indicate an increase in weekly production. D) Reject the null hypothesis; there is insufficient evidence to indicate a change in the weekly production.

828.7) Is the mean number of desks changed from 200? Test using the.05 significance level. Hypothesis Test: Mean vs. Hypothesized Value 200.000

hypothesized value

203.500

mean production

16.000

std. dev.

2.263

std. error

1.55

.0610

p-value(one-tailed, upper)

197.672

confidence interval 99% lower

209.328

confidence interval 99% upper

5.828

half-width

A) Reject the null hypothesis; there is sufficient evidence to indicate an increase in the

829)

The mean length of a candy bar is 43 millimeters. There is a concern that the settings of the machine cutting the bars have changed. Test the claim at the 0.02 level that there has been no change in the mean length. The alternate hypothesis is that there has been a change. Twelve bars (n = 12) were selected at random and their lengths are recorded. The lengths are (in millimeters) 42, 39, 42, 45, 43, 40, 39, 41, 40, 42, 43 and 42.

829.1) The mean of the sample is 41.5 and the standard deviation is 1.784. Computed t = -2.913.

Has there been a statistically significant change in the mean length of the bars? A) Yes, because the computed t lies in the rejection region. B) No, because the information given is not complete. C) No, because the computed t lies in the area to the right of -2.718. D) Yes, because 43 is greater than 41.5.

829.2) Has there been a statistically significant change in the mean length of the bars? Hypothesis Test: Mean vs. Hypothesized Value

A) B) C) D)

43.000

hypothesized value

41.500

mean length(mm)

1.784

std. dev.

0.515

std. error

-2.91

.0141

p-value(two-tailed)

Yes, because the computed t lies in the rejection region. No, because the information given is not complete. No, because the computed t lies in the area to the right of -2.718. Yes, because 43 is greater than 41.5.

830)

A machine is set to fill the small-size packages of Smarties candies with 56 candies per bag. A sample revealed: four bags of 56, two bags of 57, one bag of 55, and two bags of 58. To test the hypothesis that the mean candies per bag is 56, how many degrees of freedom are there? A) 9 B) 1 C) 8 D) 7

831)

Using a 5% level of significance and a sample size of 25, what is the critical t value for a null hypothesis, H0: µ≤ 100? A) 1.708 B) 1.711 C) 2.060 D) 2.064

For a null hypothesis, H0: µ = 4,000, if the 1% level of significance is used and the z-test statistic is + 6.00, what is our decision regarding the null hypothesis? A) Do not reject H0. B) Reject H0. C) Reject H1.

832)

833)

The ABC Pharm Co states that their anti-virus pills will remedy a patient with illness more than 89.2% of the time. In a sample of 200 cases it was documented that 182 patients were remedied.

833.1) Using an α = 0.05, what is the null hypothesis? A) P = 0.892 B) P ≠ 0.892 C) P ≥ 89.2 D) P ≤.892 E) P = 0.91

833.2) Using an α = 0.05, what is the alternative hypothesis? A) P < 0.892 B) P > 0.892 C) P ≥ 89.2 D) P ≤.892 E) P ≠ 0.91

833.3) Using an α = 0.05, compute the standard error of the proportion A) 0.0219 B) 0.0239 C) .0252 D) .0000

833.4) Using an α = 0.05, compute the test statistic. A) 0.82 B) 1.50 C) 1.82 D) 2.37

834)

The ABC Pharm Co states that their anti-virus pills will remedy a patient with illness more than 87.5% of cases. In a sample of 200 cases it was documented that 182 patients were remedied.

834.1) Using an α = 0.05, compute the standard error of the proportion A) 0.0219 B) 0.0234 C) .0252 D) .0000

834.2) Using an α = 0.05, compute the test statistic. A) 0.82 B) 1.50 C) 1.82 D) 2.37

834.3) Using an α = 0.05, if the computed Z value = 1.50, what is the p-value and what

conclusion can you reach about the company's claim? A) The p-value is 0.1336. Since the value is > than α = 0.05 reject Ho and disagree with the company's claim. B) The p-value is 0.1336. Since the value is > than α = 0.05 do not reject Ho and disagree with the company's claim. C) The p-value is 0.0668. Since the value is > than α = 0.05 do not reject Ho and disagree with the company's claim. D) The p-value is 0.0668. Since the value is > than α = 0.05 reject Ho and agree with the company's statement.

835)

The ABC Pharm Co states that their anti-virus pills will remedy a patient with illness more than 85% of cases. In a sample of 200 cases it was documented that 182 patients were remedied.

835.1) Using an α = 0.05. Compute the standard error of the proportion A) 0.0219 B) 0.0239 C) .0252 D) .0000

835.2) Using an α = 0.05. Compute the test statistic. A) 0.82 B) 1.50 C) 1.82 D) 2.38

835.3) Using an α = 0.01, state the decision rule. A) Reject the null hypothesis if the Z-Stat is > 2.58 B) Reject the null hypothesis if the Z-Stat is > 2.33 C) Reject the null hypothesis if the Z-Stat is > 2.05 D) Reject the null hypothesis if the Z-Stat is > 1.88 E) Reject the null hypothesis if the Z-Stat is > 1.75

835.4) Using an α = 0.02, state the decision rule. A) Reject the null hypothesis if the Z-Stat is > 2.58 B) Reject the null hypothesis if the Z-Stat is > 2.33 C) Reject the null hypothesis if the Z-Stat is > 2.05 D) Reject the null hypothesis if the Z-Stat is > 1.88 E) Reject the null hypothesis if the Z-Stat is > 1.75

835.5) Using an α = 0.03, state the decision rule. A) Reject the null hypothesis if the Z-Stat is > 2.58 B) Reject the null hypothesis if the Z-Stat is > 2.33 C) Reject the null hypothesis if the Z-Stat is > 2.05 D) Reject the null hypothesis if the Z-Stat is > 1.88 E) Reject the null hypothesis if the Z-Stat is > 1.75

835.6) Using an α = 0.04, state the decision rule. A) Reject the null hypothesis if the Z-Stat is > 2.58 B) Reject the null hypothesis if the Z-Stat is > 2.33 C) Reject the null hypothesis if the Z-Stat is > 2.05 D) Reject the null hypothesis if the Z-Stat is > 1.88 E) Reject the null hypothesis if the Z-Stat is > 1.75

835.7) Using an α = 0.05, state the decision rule. A) Reject the null hypothesis if the Z-Stat is > 2.58 B) Reject the null hypothesis if the Z-Stat is > 1.65 C) Reject the null hypothesis if the Z-Stat is > 1.96 D) Reject the null hypothesis if the Z-Stat is > 1.28 E) Reject the null hypothesis if the Z-Stat is > 2.05

835.8) Using an α = 0.10, state the decision rule. A) Reject the null hypothesis if the Z-Stat is > 1.96 B) Reject the null hypothesis if the Z-Stat is > 2.33 C) Reject the null hypothesis if the Z-Stat is 1.28 D) Reject the null hypothesis if the Z-Stat is > 1.88 E) Reject the null hypothesis if the Z-Stat is > 1.75

835.9) Using an α = 0.05, if the computed Z value = 2.38, what is the p-value and what

conclusion can you reach about the company's claim? A) The p-value is 0.0178. Since the value is < than α = 0.05 reject Ho and agree with the company's claim B) The p-value is 0.0087. Since the value is < than α = 0.05 reject Ho and agree with the company's statement C) The p-value is 0.0087. Since the value is < than α = 0.05 do not reject Ho and disagree with the company's claim D) The p-value is 0.0178. Since the value is < than α = 0.05 do not reject Ho and disagree the company's claim

Answer Key Test name: chapter 9 158) D 159) A 160) A 161) C 162) C 163) D 164) D 165) A 166) C 167) A 168) D 169) A 170) A 171) Section Break 171.1) D 171.2) E 171.3) B 171.4) C 171.5) B 171.6) D 172) D 173) A 174) E 175) A 176) A 177) Section Break 177.1) C 177.2) C 177.3) B 178) A 179) C 180) A 181) C 182) C 183) D 184) C 185) Section Break

185.1) B 185.2) A 185.3) E 185.4) E 185.5) A 186) Section Break 186.1) B 186.2) A 186.3) A 187) Section Break 187.1) B 187.2) B 187.3) E 188) C 189) B 190) A 191) E 192) A 193) E 194) A 195) B 196) D 197) C 198) D 199) B 200) C 201) D 202) D 203) C 204) B 205) Section Break 205.1) B 205.2) A 205.3) A 206) B 207) B 208) A 209) D 210) Section Break 210.1) B

210.2) A 210.3) A 211) Section Break 211.1) A 211.2) B 211.3) C 211.4) D 211.5) B 211.6) C 211.7) A 211.8) A 211.9) C 212) Section Break 212.1) A 212.2) A 212.3) A 212.4) A 213) Section Break 213.1) D 213.2) B 213.3) D 213.4) A 213.5) D 213.6) A 214) D 215) A 216) B 217) A 218) B 219) A 220) A 221) A 222) A 223) A 224) Section Break 224.1) B 224.2) C 224.3) D 224.4) C 224.5) C

224.6) B 224.7) A 225) A 226) A 227) B 228) B 229) B 230) B 231) C 232) D 233) A 234) A 235) C 236) B 237) C 238) Section Break 238.1) B 238.2) B 238.3) B 239) C 240) Section Break 240.1) B 240.2) D 240.3) A 240.4) A 240.5) C 240.6) C 240.7) C 241) Section Break 241.1) A 241.2) A 242) C 243) B 244) B 245) Section Break 245.1) D 245.2) B 245.3) A 245.4) A 246) Section Break

246.1) B 246.2) B 246.3) C 247) Section Break 247.1) C 247.2) D 247.3) B 247.4) C 247.5) D 247.6) E 247.7) B 247.8) C 247.9) B

Student name:__________ 836)

i. If the null hypothesis states that there is no difference between the mean income of males and the mean income of females, then the test is one-tailed. ii. If we are testing for the difference between two population means, it is assumed that the sample observations from one population are independent of the sample observations from the other population. iii. If we are testing for the difference between two population means, it is assumed that the two populations are approximately normal and have equal variances. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

837)

i. If the null hypothesis states that there is no difference between the mean income of males and the mean income of females, then the test is one-tailed. ii. If we are testing for the difference between two population means, it is assumed that the sample observations from one population are independent of the sample observations from the other population. iii. When sample sizes are less than 30, a test for the differences between two population means has n - 1 degrees of freedom. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

838)

i. If we are testing for the difference between two population means, it is assumed that the sample observations from one population are independent of the sample observations from the other population. ii. If we are testing for the difference between two population means, it is assumed that the two populations are approximately normal and have equal variances. iii. When sample sizes are less than 30, a test for the differences between two population means has n - 1 degrees of freedom. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

839)

i. If we are testing for the difference between two population means, it is assumed that the sample observations from one population are independent of the sample observations from the other population. ii. If we are testing for the difference between two population means, it is assumed that the two populations are approximately normal and have equal variances. iii. The critical value of t for a two-tail test of the difference of two means, at a level of significance of 0.10 and sample sizes of seven and fifteen is ±1.725. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

840)

i. If the null hypothesis states that there is no difference between the mean income of males and the mean income of females, then the test is one-tailed. ii. If we are testing for the difference between two population means, it is assumed that the sample observations from one population are independent of the sample observations from the other population. iii. The critical value for the claim that the difference of two means is less than zero with a level of significance of 0.025 and sample sizes of nine and seven, is -2.179. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

841)

If the null hypothesis that two means are equal is true, 97% of the computed-values will lie between what two values? A) ±2.58 B) ±2.33 C) ±2.17 D) ±2.07

842)

Using two independent samples, two population means are compared to determine if a difference exists. The number in the first sample is fifteen and the number in the second sample is twelve. How many degrees of freedom are associated with the critical value? A) 24 B) 25 C) 26 D) 27

843)

Administering the same test to a group of 15 students and a second group of 15 students to see which group scores higher is an example of: A) a one sample test of means. B) a two sample test of means. C) A paired t-test. D) a test of proportions.

844)

What is the critical value for a one-tailed hypothesis test in which a null hypothesis is tested at the 5% level of significance based on two samples, both sample sizes are 13? A) 1.708 B) 1.711 C) 2.060 D) 2.064

845)

If two samples are used in a hypothesis test for which the combined degrees of freedom is 24, which one of the following CANNOT be true about the two sample sizes? A) Sample A = 11; Sample B = 13 B) Sample A = 12; Sample B = 14 C) Sample A = 13; Sample B = 13 D) Sample A = 10; Sample B = 16

846)

If two samples are used in a hypothesis test for which the combined degrees of freedom is 27, which one of the following might be true about the two sample sizes? A) Sample A = 14; Sample B = 13 B) Sample A = 12; Sample B = 13 C) Sample A = 15; Sample B = 14 D) Sample A = 20; Sample B = 8

847)

The net weights of a sample of bottles filled by a machine manufactured by Edne, and the net weights of a sample filled by a similar machine manufactured by Orno, Inc., are (in grams): Edne

5,8,7,6,9 and 7

Orno

8,10,7,11,9,12,14 and 9

Testing the claim at the 0.05 level the mean weight of the bottles filled by the Orno machine is greater than the mean weight of the bottles filled by the Edne machine, what is the critical value? A) -1.96 B) -2.837 C) -6.271 D) + 3.674 E) + 1.782

848)

Which of the following conditions must be met to conduct a test for the difference in two sample means? A) Data must be at least of interval scale. B) Populations must be normal. C) Variances in the two populations must be equal. D) Populations must be normal, the variances must be equal and the two samples must be unrelated, that is, independent.

849)

A national manufacturer of ball bearings is experimenting with two different processes for producing precision ball bearings. It is important that the diameters be as close as possible to an industry standard. The output from each process is sampled and the average error from the industry standard is calculated. The results are presented below: Process A

Process B

Mean

0.002mm

0.0026mm

Standard Deviation

0.0001mm

0.00012mm

Sample Size

849.1) The researcher is interested in determining whether there is evidence that the two

processes yield different average errors. Ball Bearings Hypothesis Test: Independent Groups (t-test, pooled variance) Process A

Process B

0.002

0.0026

mean

0.0001

0.00012

std. dev.

-0.0006000

difference (Process A - Process B)

0.0000000

pooled variance

0.0001113

Pooled std. dev.

0.0000438

standard error of difference

hypothesized difference

-13.71

7.61E-13

p-value(two-tailed)

-0.0006904 -0.0005096 0.0000904

half-width

What is the decision at the 1% level of significance? A) Reject the null hypothesis and conclude the means are different. B) Reject the null hypothesis and conclude the means are the same. C) Fail to reject the null hypothesis and conclude the means are the same. D) Fail to reject the null hypothesis and conclude the means are different.

849.2) The researcher is interested in determining whether there is evidence that the two

processes yield different average errors. Given the following MegaStat printout, what analysis and decision can be made? Hypothesis Test: Independent Groups (t-test, pooled variance) Process A

Process B

0.002

0.0026

mean

0.0001

0.00012

std. dev.

-0.0006000

difference (Process A Process B)

0.0000000

pooled variance

0.0001113

Pooled std. dev.

0.0000438

standard error of difference

hypothesized difference

-13.71

7.61E-13

p-value(two-tailed)

The researcher is interested in determining whether there is evidence that the two processes yield different average errors. A) Reject the null hypothesis and conclude the means are different. B) Reject the null hypothesis and conclude the means are the same. C) Fail to reject the null hypothesis at the 1% level of significance. D) Fail to reject the null hypothesis at the 5% level of significance and conclude the means are different.

849.3) What is the null hypothesis? A) µA - µB = 0 B) µA - µB ≠ 0 C) µA - µB ≤ 0 D) µA - µB > 0

849.4) What is the alternative hypothesis? A) µA - µB = 0 B) µA ≠ µB C) µA - µB ≤ 0 D) µA - µB > 0

849.5) There are how many degrees of freedom? A) 10 B) 13 C) 26 D) 24

849.6) What is the critical t value at the 1% level of significance? A) + 2.779 B) -2.492 C) ±1.711 D) ±2.797

849.7) What is the computed value of t? A) + 2.797 B) -2.797 C) -13.71 D) + 13.71

849.8) What is the decision at the 1% level of significance? A) Reject the null hypothesis and conclude the means are different. B) Reject the null hypothesis and conclude the means are the same. C) Fail to reject the null hypothesis and conclude the means are the same. D) Fail to reject the null hypothesis and conclude the means are different.

849.9) Assume calculated t to be + 2.70; what is the decision at the 0.01 level of significance? A) Reject the null hypothesis and conclude the means are different. B) Reject the null hypothesis and conclude the means are the same. C) Fail to reject the null hypothesis and conclude the means are the same. D) Fail to reject the null hypothesis and conclude the means are different.

849.10) This example is what type of test? A) One sample test of means. B) Two sample test of means. C) Paired t-test. D) Test of proportions.

849.11) If you were to use MegaStat to assist in your solution to this problem, which test would

you use? A) Mean vs. Hypothesized value. B) Compare two independent groups. C) Paired observations. D) Proportion vs. Hypothesized value. E) Compare two independent proportions. F) Chi-square variance test

850)

The results of a mathematics placement exam at Mercy College for two campuses are as follows: Campus

Number

Mean

Std. Deviation

330

310

850.1) What is the null hypothesis if we want to test the hypothesis that the mean score on

Campus 1 is higher than on Campus 2? A) µ1 = 0 B) µ2 = 0 C) µ1 = µ2 D) µ1 > µ2 E) µ1 ≤ µ2

850.2) What is the computed value of the test statistic? A) 9.3 B) 2.6 C) 3.4 D) 1.9

850.3) What is the p-value if the computed test statistic is 4.1? A) 1.0 B) 0.0 C) 0.05 D) 0.95

850.4) If you were to use MegaStat to assist in your solution to this problem, which test would

850.5) We want to test the hypothesis that the mean score on Camp us 1 is higher than on

Campus 2. Hypothesis Test: Independent Groups (z-test) 1

mean

std. dev.

330

310

2.000

difference (1 -2)

0.593

standard error of difference

hypothesized difference

3.37

.0004

p-value(one-tailed, upper)

Using the printout above, what decision(s) can be made? A) Looking at the P-value we conclude that there is no significant difference in the results from each campus. B) At a 5% level of significance we conclude that there is no significant difference in the results from each campus. C) At a 1% level of significance we conclude that campus 1 results are higher than campus 2 results. D) Looking at the P-value we conclude that there is no significant difference in the results from each campus; we get the same conclusion when tested at a 5% level of significance. E) Looking at the P-value we conclude that there is no significant difference in the results from each campus; however, at a 1% level of significance we conclude that campus 1 results are higher than campus 2 results.

851)

i. A committee studying employer-employee relations proposed that each employee would rate his or her immediate supervisor and in turn the supervisor would rate each employee. To find reactions regarding the proposal, 120 office personnel and 160 plant personnel were selected at random. Seventy-eight of the office personnel and 90 of the plant personnel were in favour of the proposal. Computed z = 1.48. At the 0.05 level, it was concluded that there is sufficient evidence to support the belief that the proportion of office personnel in favour of the proposal is greater than that of the plant personnel. ii. We use the pooled estimate of the proportion in testing the difference between two population proportions. iii. The pooled estimate of the proportion is found by dividing the total number of samples by the total number of successes. A) (i), (ii), and (iii) are all false statements. B) (ii) is a correct statement but not (i) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i) is a correct statement but not (ii) and (iii).

852)

i. We use the pooled estimate of the proportion in testing the difference between two population proportions when the samples are not chosen independently. ii. The pooled estimate of the proportion is found by dividing the total number of samples by the total number of successes. iii. A committee studying employer-employee relations proposed that each employee would rate his or her immediate supervisor and in turn the supervisor would rate each employee. To find reactions regarding the proposal, 120 office personnel and 160 plant personnel were selected at random. Seventy-eight of the office personnel and 90 of the plant personnel were in favour of the proposal. Computed z = 1.48. At the 0.05 level, it was concluded that there is sufficient evidence to support the belief that the proportion of office personnel in favour of the proposal is greater than that of the plant personnel. A) (i), (ii), and (iii) are all false statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i) is a correct statement, but not (ii) and (iii).

853)

If the decision is to reject the null hypothesis at the 5% level of significance, what are the acceptable alternate hypothesis and rejection region? A) p1 ≠ p2; z > 1.65 and z < -1.65 B) p1 ≠ p2; z > 1.96 and z < -1.96 C) p1 > p2; z < -1.65 D) p1 > p2; z < -1.96

854)

A poll of 400 people from village 1 showed 250 preferred chocolate raspberry coffee to the regular blend while 170 out of 350 in village 2 preferred the same flavour. To test the hypothesis that there is no difference in preferences in the two villages, what is the alternative hypothesis? A) p1 < p2 B) p1 > p2 C) p1 = p2 D) p1 ≠ p2

855)

856)

How is a pooled estimate represented? A) pc B) z C) p D) n p

Suppose we are testing the difference between two proportions at the 0.05 level of significance. If the computed z is -1.07, what is our decision? A) Reject the null hypothesis. B) Do not reject the null hypothesis. C) Take a larger sample. D) Reserve judgment.

857)

To compare the effect of weather on sales of soft drinks, a soda manufacturer sampled two regions of the country with the following results. Is there a difference in sales between the 2 regions? Region A

Region B

Sample Size

1000

1500

Sales

400

500

857.1) i. The null hypothesis is pa = pb

ii. The alternative hypothesis is pa ≠ pb iii. The proportion of sales made in Market Area 1 is 0.45. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.2) i. The null hypothesis is pa = pb

ii. The alternative hypothesis is pa ≠ pb iii. The proportion of sales made in Market Area 2 is 0.33. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.3) i. The null hypothesis is pa > pb

ii. The alternative hypothesis is pa pb iii. The pooled estimate of the population proportion is 0.36. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.4) i. The null hypothesis is pa = pb

ii. The alternative hypothesis is pa ≠ pb iii. Using the 1% level of significance, the critical value is ±2.58. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.5) i. The null hypothesis is pa = pb

ii. The alternative hypothesis is pa > pb iii. The z-statistic is 3.40. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.6) i. The null hypothesis is pa = pb

ii. The alternate hypothesis is pa - pb ≠ 0. iii. If α = 0.01 and the z-statistic was calculated to be -1.96, your decision would be to fail to reject. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.7) i. The alternative hypothesis is pa ≠ pb

ii. The proportion of sales made in Market Area 1 is 0.40. iii. The proportion of sales made in Market Area 2 is 0.33. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.8) i. The alternative hypothesis is pa ≠ pb

ii. The pooled estimate of the population proportion is 0.36. iii. Using the 1% level of significance, the critical value is ±1.96. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.9) i. The alternative hypothesis is pa ≠ pb

ii. Using the 1% level of significance, the critical value is ±2.58. iii. The z-statistic is 3.40. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.10) i. Using the 1% level of significance, the critical value is ±2.58.

ii. The z-statistic is 3.40. iii. Your decision is to reject the null hypothesis. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

857.11) i. The alternative hypothesis is pa > pb

ii. The z-statistic is 3.40. iii. Your decision is to accept the null hypothesis. A) (i), (ii) and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

858)

Of 250 adults who tried a new multi-grain cereal, Wow! 187 rated it excellent; of 100 children sampled, 66 rated it excellent. Using the 0.1 significance level and the alternate hypothesis p1 does not equal p2, what is the null hypothesis? A) p1 ≥ p2 B) p1 ≤ p2 C) p1 = p2

859)

Of 250 adults who tried a new multi-grain cereal, Wow!, 187 rated it excellent; of 100 children sampled, 66 rated it excellent. What test statistic should we use? A) z-statistic B) Right one-tailed test C) Left one-tailed test D) Two-tailed test

860)

A recent study compared the time spent together by single and dual-earner couples. According to the records kept during the study, the mean amount of time spent together watching TV among single-earner couples was 64 minutes per day, with a standard deviation of 15.5 minutes. For the dual-earner couples, the mean time was 48.4 and the standard deviation was 18.1. At a 0.01 significance level, can we conclude that the single-earner couples on average spend more time watching TV together?

860.1) There were 20 single-earner and 12 dual-earner couples studied. State the decision rule,

the value of the test statistic, and your decision. A) Reject if t > 2.457, t = 2.59, single-earner couples spend more time watching TV together. B) Reject if t > 2.508, t = 0.96, insufficient evidence to say that single-earner couples spend more time watching TV together. C) Reject if t > 2.797, t = 2.57, single-earner couples spend more time watching TV together. D) Reject if t > 2.042, t = 1.96, insufficient evidence to say that single-earner couples spend more time watching TV together. E) Reject if t > 2.485, t = 2.77, single-earner couples spend more time watching TV together.

860.2) There were 12 single-earner and 12 dual-earner couples studied. State the decision rule,

the value of the test statistic, and your decision. A) Reject if t > 2.485, t = 2.77, single-earner couples spend more time watching TV together. B) Reject if t > 2.508, t = 1.96, insufficient evidence to say that single-earner couples spend more time watching TV together. C) Reject if t > 2.797, t = 2.57, single-earner couples spend more time watching TV together. D) Reject if t > 2.508, t = 1.69, insufficient evidence to say that single-earner couples spend more time watching TV together. E) Reject if t > 2.508, t = 2.27, insufficient evidence to say that single-earner couples spend more time watching TV together.

860.3) There were 15 single-earner and 12 dual-earner couples studied. State the decision rule,

the value of the test statistic, and your decision. A) Reject if t > 2.485, t = 2.41, insufficient evidence to say that single-earner couples spend more time watching TV together. B) Reject if t > 2.485, t = 2.11, insufficient evidence to say that single-earner couples spend more time watching TV together. C) Reject if t > 2.473, t = 1.95, insufficient evidence to say that single-earner couples spend more time watching TV together. D) Reject if t > 2.473, t = 2.55, single-earner couples spend more time watching TV together. E) Reject if t > 2.485, t = 2.60, single-earner couples spend more time watching TV together.

860.4) There were 15 single-earner and 15 dual-earner couples studied. State the decision rule,

the value of the test statistic, and your decision. A) Reject if t > 2.485, t = 2.01, single-earner couples spend more time watching TV together. B) Reject if t > 2.473, t = 1.95, insufficient evidence to say that single-earner couples spend more time watching TV together. C) Reject if t > 2.473, t = 2.57, single-earner couples spend more time watching TV together. D) Reject if t > 2.457, t = 2.53, insufficient evidence to say that single-earner couples spend more time watching TV together. E) Reject if t > 2.467, t = 2.54, single-earner couples spend more time watching TV together.

860.5) There were 9 single-earner and 11 dual-earner couples studied. State the decision rule,

the value of the test statistic, and your decision. A) Reject if t > 2.485, t = 2.57, insufficient evidence to say that single-earner couples spend more time watching TV together. B) Reject if t > 2.552, t = 2.04, insufficient evidence to say that single-earner couples spend more time watching TV together. C) Reject if t > 2.552, t = 2.04, single-earner couples spend more time watching TV together. D) Reject if t > 2.508, t = 0.96, single-earner couples spend more time watching TV together. E) Reject if t > 2.485, t = 2.01, single-earner couples spend more time watching TV together.

861)

Of 150 adults who tried a new peach-flavoured peppermint patty, 99 rated it excellent. Of 200 children sampled, 123 rated it excellent. Using the 0.10 level of significance, can we conclude that there is a significant difference in the proportion of adults and the proportion of children who rate the new flavour as excellent? State the decision rule, the value of the test statistic, and your decision. A) Reject if z > 1.96 or < -1.96, z = -2.26, difference exists. B) Reject if z > 1.96 or < -1.96, z = -0.66, no difference. C) Reject if z > 1.645 or < -1.645, z = 0.87, difference exists. D) Reject if z > 1.645 or < -1.645, z = -0.28, difference exists. E) Reject if z > 1.645 or < -1.645, z = 0.87, no difference.

862)

Of 150 adults who tried a new peach-flavoured peppermint patty, 90 rated it excellent. Of 200 children sampled, 123 rated it excellent. Using the 0.10 level of significance, can we conclude that there is a significant difference in the proportion of adults and the proportion of children who rate the new flavour as excellent? State the decision rule, the value of the test statistic, and your decision. A) Reject if z > 1.645 or < -1.645, z = -0.28, difference exists B) Reject if z > 1.645 or < -1.645, z = -0.28, no difference. C) Reject if z > 1.645 or < -1.645, z = -1.28, difference exists. D) Reject if z > 1.96 or < -1.96, z = -0.66, no difference. E) Reject if z > 1.96 or < -1.96, z = -2.26, difference exists.

863)

Of 150 adults who tried a new peach-flavoured peppermint patty, 81 rated it excellent. Of 200 children sampled, 123 rated it excellent. Using the 0.10 level of significance, can we conclude that there is a significant difference in the proportion of adults and the proportion of children who rate the new flavour as excellent? State the decision rule, the value of the test statistic, and your decision. A) Reject if z > 1.645 or < -1.645, z = -1.28, no difference. B) Reject if z > 1.645 or < -1.645, z = -1.28, difference exists. C) Reject if z > 1.96 or < -1.96, z = -0.66, no difference. D) Reject if z > 1.96 or < -1.96, z = -1.41, difference exists. E) Reject if z > 1.645 or < -1.645, z = -1.41, no difference.

864)

Of 150 adults who tried a new peach-flavoured peppermint patty, 75 rated it excellent. Of 200 children sampled, 123 rated it excellent. Using the 0.10 level of significance, can we conclude that there is a significant difference in the proportion of adults and the proportion of children who rate the new flavour as excellent? State the decision rule, the value of the test statistic, and your decision. A) Reject if z > 1.645, z = -0.66, no difference. B) Reject if z > 1.645 or < -1.645, z = -5.28, difference exists. C) Reject if z > 1.96 or < -1.96, z = -2.15 no difference. D) Reject if z > 1.96 or < -1.96, z = -2.26, difference exists. E) Reject if z > 1.645 or < -1.645, z = -2.15, difference exists.

865)

Of 150 adults who tried a new peach-flavoured peppermint patty, 87 rated it excellent. Of 200 children sampled, 123 rated it excellent. Using the 0.10 level of significance, can we conclude that there is a significant difference in the proportion of adults and the proportion of children who rate the new flavour as excellent? State the decision rule, the value of the test statistic, and your decision. A) Reject if z > 1.645 or < -1.645, z = -0.66, no difference. B) Reject if z > 1.645, z = -0.66, no difference. C) Reject if z > 1.645 or < -1.645, z = -5.28, difference exists. D) Reject if z > 1.96 or < -1.96, z = -0.66, no difference. E) Reject if z > 1.96 or < -1.96, z = -2.26, difference exists.

866)

i. If samples taken from two populations are not independent, then a test of paired differences is applied. ii. The paired difference test has ( n1 + n2 - 2) degrees of freedom. iii. The paired t test is especially appropriate when the sample sizes of two groups are the same. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i) is a correct statement but not (ii) and (iii).

867)

i. If samples taken from two populations are not independent, then a test of paired differences is applied. ii. The paired difference test has ( n1 + n2 - 2) degrees of freedom. iii. A statistics professor wants to compare grades of two different groups of students taking the same course in two different sections. This is an example of a paired sample. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) is a correct statement but not (ii) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

868)

i. The paired difference test has ( n1 + n2 - 2) degrees of freedom. ii. The paired t test is especially appropriate when the sample sizes of two groups are the same. iii. A statistics professor wants to compare grades of two different groups of students taking the same course in two different sections. This is an example of a paired sample. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

869)

i. If samples taken from two populations are not independent, then a test of paired differences is applied. ii. The paired difference test has ( n - 1) degrees of freedom. iii. The paired t test is especially appropriate when the sample sizes of two groups are the same. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but not (i) and (iii).

870)

A poll of 400 people from village 1 showed 250 preferred chocolate raspberry coffee to the regular blend while 170 out of 350 in village 2 preferred the same flavor. You wish to test the hypothesis that there is no difference in preferences in the two villages. If you were to use Excel's MegaStat to assist in your solution to this problem, which test would you use? A) Mean vs. Hypothesized value. B) Compare two independent groups. C) Paired observations. D) Proportion vs. Hypothesized value. E) Compare two independent proportions. F) Chi-square variance test.

871)

872)

When is it appropriate to use the paired difference t-test? A) Four samples are compared at once. B) Any two samples are compared. C) Two independent samples are compared. D) Two dependent samples are compared.

A random sample of 20 statistics students was given 15 multiple-choice questions and 15 open-ended questions-all on the same material. The professor was interested in determining which type of questions the students scored higher. This experiment is an example of: A) a one sample test of means. B) a two sample test of means. C) A paired t-test. D) a test of proportions.

873)

A random sample of 20 statistics students were given 15 multiple-choice questions and 15 open-ended questions-all on the same material. The professor was interested in determining which type of questions the students scored higher. If you were to use MegaStat to assist in your solution to this problem, which test would you use? A) Mean vs. Hypothesized value. B) Compare two independent groups. C) Paired observations. D) Proportion vs. Hypothesized value. E) Compare two independent proportions. F) Chi-square variance test

874)

A local retail business wishes to determine if there is a difference in preferred indoor temperature between men and women. A random sample of data is collected, with the following results: Hypothesis Test: Independent Groups (t-test, pooled variance) Men

Women

20.336

20.773

mean

1.529

1.272

std. dev.

-0.4364

difference (Men-Women)

1.9774

pooled variance

1.4062

Pooled std. dev.

0.5996

standard error of difference

hypothesized difference

-0.73

.4752

p-value(two-tailed)

-1.6871

confidence interval 95% lower

0.8144

confidence interval 95% upper

1.2507

half-width

What is the decision at the 5% level of significance? A) Since the p-value is large at 0.4752, we fail to reject the null hypothesis and conclude that there is no significant difference in the preferred room temperatures between the sexes. B) Since the p-value is small at 0.4752, we reject the null hypothesis and conclude that there is a significant difference in the preferred room temperatures between the sexes. C) Since the calculated t-value is more than the critical t-value, we reject the null hypothesis and conclude that there is a significant difference in the preferred room temperatures between the sexes.

D) Since the calculated t-value is more than the critical t-value, we fail to reject the null

hypothesis and conclude that there is a significant difference in the preferred room temperatures between the sexes. E) There is insufficient information to make a decision.

875)

Women

20.6

22.5

19.5

17.7

18.9

19.5

21.5

20.5

875.1) If you were to use Excel's Data Analysis to assist in your solution to this problem, which

test would you use? A) T-test: paired 2-sample for means. B) T-test: 2-sample assuming equal variances. C) T-test: 2-sample assuming unequal variances. D) Z-test: 2-sample for mean. E) F-test: 2-sample for variances.

875.2) If you were to use Megastat to assist in your solution to this problem, which test would

876)

Married women are more often than not working outside the home on at least a part-time basis, as do most mannered men. Does a husband's employment status affect his wife's wellbeing? In an attempt to answer this question, 75 married female professionals were surveyed as to their job satisfaction. In this sample, 45 husbands were employed, and 30 were unemployed. The Learning Objective of the study was to compare the mean job satisfaction levels of the married women with working husbands, with the mean job satisfaction levels of the married women with husbands that stayed at home.

876.1) The test statistic for this problem has what type of distribution? A) Normal z B) Student's t C) Positively skewed D) Negatively skewed E) Binomial

876.2) If you were to use Excel's Data Analysis to assist in your solution to this problem, which

876.3) If you were to use MegaStat to assist in your solution to this problem, which test would

877)

Accounting procedures allow a business to evaluate their inventory at LIFO (Last In First Out) or FIFO (First In First Out). A manufacturer evaluated its finished goods inventory (in $1000) for five products both ways. Based on the following results, is LIFO more effective in keeping the value of his inventory lower? Product

FIFO (F)

LIFO (L)

225

221

119

100

113

212

200

248

245

877.1) What is the null hypothesis? A) µd = 0 B) µLF ≠ µ C) µL > µF D) µd ≥ 0

877.2) What is the alternative hypothesis? A) µd = 0 B) µd ≠ 0 C) µd < 0 D) µL - µF ≠ 0

877.3) What is the degree of freedom? A) 4 B) 5 C) 15 D) 10 E) 9

877.4) If you use the 5% level of significance, what is the critical t value? A) -2.015 B) -2.132 C) -2.571 D) ±2.2 E) + 2.132

877.5) What is the value of calculated t? A) -0.93 B) ±2.776 C) + 0.47 D) -2.028

877.6) What is the decision at the 5% level of significance? A) Fail to reject the null hypothesis and conclude LIFO is more effective. B) Reject the null hypothesis and conclude LIFO is more effective. C) Reject the alternate hypothesis and conclude LIFO is more effective. D) Fail to reject the null hypothesis and conclude LIFO is not more effective.

877.7) This example is what type of test? A) One sample test of means. B) Two sample test of means. C) Paired t-test. D) Test of proportions.

877.8) If you were to use Megastat to assist in your solution to this problem, which test would

877.9) What is the decision at the 5% level of significance? FIFO vs LIFO Hypothesis Test: Paired Observations

A) B) C) D)

0.000

hypothesized value

180.800

mean FIFO (F)

175.800

mean LIFO (L)

-5.000

mean difference (LIFO(L)-FIFO(F))

11.979

std. dev.

5.357

std. error

-0.93

.2017

p-value (one-tailed, upper)

Looking at the large P-value of.2019 we conclude LIFO is more effective. Reject the null hypothesis and conclude LIFO is more effective. Reject the alternate hypothesis and conclude LIFO is more effective. The large P-value of.2017 indicates that there is a good chance of getting this sample data when the two methods are in fact not significantly different, so we conclude that LIFO is not more effective.

878)

The employees at the East Vancouver office of a multinational company are demanding higher salaries than those offered at the company office located in Oshawa Ontario. Their justification for the pay difference is that the difference between the average price of singlefamily houses in East Vancouver and that in Oshawa is more than $60,000. Before making a decision, the company management wants to study the difference in the prices of singlefamily houses for sale at the two locations. The results of their search of recent house sales are as follows (in $1000, rounded to the nearest thousand): East Vancouver 945 890 879 859 1,010 774 852 1,055 828 669 Oshawa

819 722 800 734

779

804 729

732

774 742 736 759 768 770 827

Assuming that the population distributions are approximately normal, can we conclude at the 0.05 significance level that the difference between the two population means is greater than $60,000?

878.1) If we let East Vancouver be population 1 and Oshawa be population 2, what is the null

hypothesis? A) µ1 = µ2, or µd = 0 B) µ1 ≠ µ2, or µd ≠ 0 C) µ1 - µ2 ≤ 60 D) µ1 - µ2 > 60

878.2) What is the alternative hypothesis? A) µ1 = µ2, or µd = 0 B) µ1 ≠ µ2, or µd ≠ 0 C) µ1 - µ2 ≤ 60 D) µ1 - µ2 > 60

878.3) What is the degree of freedom? A) 4 B) 5 C) 15 D) 23 E) 9

878.4) If you use the 10% level of significance, what is the critical t value? A) 2.228 B) 1.714 C) 1.319 D) ±2.262

878.5) What is the value of calculated t? A) + 1.64 B) + 3.22 C) -2.76 D) -2.028

878.6) What is the decision at the 10% level of significance? A) Fail to reject the null hypothesis and conclude that the average house prices in East

Vancouver are not more than $60,000 greater than those in Oshawa. B) Reject the null hypothesis and conclude that the average house prices in East Vancouver are not more than $60,000 greater than those in Oshawa. C) Reject the null hypothesis and conclude that the average house prices in East Vancouver are $60,000 greater than those in Oshawa. D) Fail to reject the null hypothesis and conclude that the average house prices in East Vancouver are more than $60,000 greater than those in Oshawa.

878.7) This example is what type of test? A) One sample test of means. B) Two sample test of means. C) Paired t-test. D) Test of proportions.

879)

The employees at the East Vancouver office of a multinational company are demanding higher salaries than those offered at the company office located in Oshawa Ontario. Their justification for the pay difference is that the difference between the average price of singlefamily houses in East Vancouver and that in Oshawa is more than $60,000. Before making a decision, the company management wants to study the difference in the prices of singlefamily houses for sale at the two locations. The results of their search of recent house sales are as follows (in $1000, rounded to the nearest thousand): Hypothesis Test: Independent Groups (t-test, pooled variance) East Vancouver

Oshawa

876.1

766.3

mean

111.24792

34.217094

std. dev.

109.76

difference (East Vancouver Oshawa)

30.428847

Standard Error

hypothesized difference

1.635

.0.0578

p-value (one-tailed, upper)

879.1) If you were to use MegaStat to assist in your solution to this problem, which test would

879.2) What is the decision at the 10% level of significance? A) Fail to reject the null hypothesis and conclude that the average house prices in East

Vancouver are not more than $60,000 greater than those in Oshawa. B) Since the P-value is less than the t-stat we conclude that the average house prices in East Vancouver are not more than $60,000 greater than those in Oshawa. C) Since the P-value is < than the significance level, we conclude that the average house prices in East Vancouver are $60,000 greater than those in Oshawa. D) Conclude that the average house prices in East Vancouver are different than those in Oshawa.

880)

A local retail business wishes to determine if there is a difference in preferred indoor temperature between men and women. A random sample of data is collected, with the following results (note: there are slight differences between Excel and MegaStat output in this test): t-Test: Two-Sample Assuming Unequal Variances Men

Women

Mean

20.3

20.8

Variance

2.3

1.6

Observations

Hypothesized Mean Difference

t Stat

-0.72776

P(T≤t) one-tail

0.237818

t Critical one-tail

1.729131

P(T≤t) two-tail

0.475636

t Critical two-tail

2.093025

880.1) Using a 0.05 level of significance, can we conclude that there is indeed a difference in the

temperature that men prefer compared to women? What is the null hypothesis if we assume men to be group 1 and women group 2? A) µ1 = µ2, or µd = 0 B) µ1 ≠ µ2, or µd ≠ 0 C) µ1 - µ2 ≤ 20 D) µ1 - µ2 > 20

880.2) What is the alternate hypothesis? A) µ1 - µ2 > 0, or µd > 0 B) µ1 ≠ µ2, or µd ≠ 0 C) µ1 - µ2 ≤ 0, or µd < 0 D) µ1 - µ2 = 0

880.3) What is the degree of freedom? A) 11 B) 22 C) 21 D) 20 E) 19

880.4) If you use the 5% level of significance, what is the critical t value? A) ±2.093 B) ±2.086 C) ±1.729 D) ±1.725

880.5) What is the decision at the 5% level of significance? A) Since the calculated t-value is less than the critical t-value, fail to reject the null

hypothesis and conclude that there is no significant difference in the preferred room temperatures between the sexes. B) Since the calculated t-value is less than the critical t-value, we reject the null hypothesis and conclude that there is a significant difference in the preferred room temperatures between the sexes. C) Since the calculated t-value is more than the critical t-value, we reject the null hypothesis and conclude that there is a significant difference in the preferred room temperatures between the sexes. D) Since the calculated t-value is more than the critical t-value, we fail to reject the null hypothesis and conclude that there is a significant difference in the preferred room temperatures between the sexes. E) There is insufficient information to make a decision.

881)

Married women are more often than not working outside the home on at least a part-time basis, as do most men. Does a husband's employment status affect his wife's well-being? In an attempt to answer this question, 20 married female professionals were surveyed as to their job satisfaction. In this sample, 15 husbands were employed, and 5 were unemployed. The Learning Objective of the study was to compare the mean job satisfaction levels of the married women with working husbands, with the mean job satisfaction levels of the married women with husbands that stayed at home.

881.1) Set up the hypotheses to test whether the job satisfaction levels of married women with

working husbands is any more than that of their counterparts with unemployed husbands. A) H0: µE = µU, H1: µE ≠ µU, or B) H0: µd ≤0, H1: µd > 0 C) H0: µE ≤ µU, H1: µE > µU, D) H0: µE ≠ µU, H1: µE > µU, or E) H0: µE ≠ µU, H1: µE < µU, or H0: µd ≠ 0, H1: µd < 0

881.2) The test statistic for this problem has what type of distribution? A) Normal z B) Student's t C) Positively skewed. D) Negatively skewed. E) Binomial

881.3) If the p-value obtained from the computer printout is 0.025, does this give sufficient

evidence to conclude that the mean level of job satisfaction for women with working husbands is more than that of those whose husbands don't work? A) Yes, at alpha = 0.05. B) Yes, at alpha = 0.01. C) No, at alpha = 0.10. D) No, at alpha = 0.04. E) Insufficient information to make a decision.

881.4) If the p-value obtained from the computer printout is 0.055, does this give sufficient

evidence to conclude that the mean level of job satisfaction for women with working husbands is more than that of those whose husbands don't work? A) Yes, at alpha = 0.05. B) Yes, at alpha = 0.01. C) Yes, at alpha = 0.10. D) No, at alpha = 0.06. E) Insufficient information to make a decision.

882)

Suppose we test H0: P1 = P2 at the 0.05 level of significance. If the z-test statistic is 1.07, what is our decision? A) Reject the null hypothesis. B) Do not reject the null hypothesis. C) Take a larger sample. D) Reserve judgment.

883)

The net weights (in grams) of a sample of bottles filled by a machine manufactured by Edne, and the net weights of a sample filled by a similar machine manufactured by Orno, Inc., are: Edne

Orno

Testing the claim at the 0.05 level that the mean weight of the bottles filled by the Orno machine is greater than the mean weight of the bottles filled by the Edne machine, what is the critical value oft? Assume equal standard deviations for both samples. A) + 2.179 B) + 2.145 C) + 1.782 D) + 1.761

For a hypothesis comparing two population means, H0: μ1≤ μ2, what is the critical value for a one-tailed hypothesis test, using a 5% significance level, with both sample sizes equal to 13? Assume the population standard deviations are equal. A) ±1.711 B) + 1.711 C) + 2.060 D) + 2.064

884)

885)

An investigation of the effectiveness of a training program to improve customer relationships included a pre-training and post-training customer survey. To compare the differences, they computed (post-training survey score - pre-training survey score). Seven customers were randomly selected and completed both surveys. The results follow: Customer

Pre-training Survey

Post-training Survey

885.1) This analysis is an example of: A) a one-sample test of means B) a two-sample test of means C) a paired t-test D) a test of proportions

885.2) For a 0.05 significance level, determine the critical value and the calculated value of the

test statistic for an improvement in customer relations after training? A) 1.943; 2.542 B) 1.895; 2.542 C) 1.645; 2.447 D) 2.447; 1.943

885.3) Was the training effective in improving customer relationships when tested at a 0.05 level

of significance? A) Reject the null hypothesis and conclude that the training was effective. B) Reject the null hypothesis and conclude that the training was ineffective. C) Fail to reject the null hypothesis and conclude that mean survey scores are the same. D) Fail to reject the null hypothesis and conclude that the mean survey scores are not equal.

885.4) Determine the calculated value of t. Was the training effective in improving customer

relationships when tested at a 0.01 level of significance? A) 2.542; t-critical = 3.707. Reject the null hypothesis and conclude that the training was effective B) 2.542; t- critical = 3.707 Reject the null hypothesis and conclude that the training was ineffective C) 2.542, t-critical = 3.707; Fail to reject the null hypothesis and conclude that the training was ineffective D) 2.542; Fail to reject the null hypothesis and conclude that the mean survey scores are not equal. E) 2.447; Reject the null hypothesis and conclude that the training was effective

885.5) The calculated value of t. is 2.542. Was the training effective in improving customer

relationships when tested at a 0.05 level of significance? A) Reject the null hypothesis and conclude that the training was effective B) Reject the null hypothesis and conclude that the training was ineffective C) Fail to reject the null hypothesis and conclude that mean survey scores are the same D) Fail to reject the null hypothesis and conclude that the mean survey scores are not equal.

886)

A company is researching the effectiveness of a new website design to decrease the time to access a website. Five website users were randomly selected and their times (in seconds) to access the website with the old and new designs were recorded. To compare the times, they computed (new website design time - old website design time). The results follow: User

Old Website Design

New Website Design

886.1) What are the null and alternative hypothesis? A) H0: µ d = 0; H1: µd ≠ 0 B) H0: µ d ≠ 0; H1: µd = 0 C) H0: µ d ≤ 0; H1: µd > 0 D) H0: µ d ≥ 0; H1: µd ≠ 0 E) H0: µ d ≥ 0; H1: µd < 0

886.2) What is the value of the calculated test statistic? A) -2.256 B) 1.895 C) -3.747 D) 2.447

886.3) For a 0.01 significance level, what is the critical value? A) -2.256 B) 1.895 C) -3.747 D) 2.447

886.4) If the calculated test statistic is -2.256, what is the decision regarding the hypothesis that

the new website was effective decreasing time to access the website when tested at 0.05 significance level? A) Reject the null hypothesis and conclude that the new design reduced mean access times. B) Reject the null hypothesis and conclude that the new design did not reduce mean access times. C) Fail to reject the null hypothesis and conclude that the new design did not reduce mean access times. D) Fail to reject the null hypothesis and conclude that the mean access times are inaccurate.

887)

As we move into the endemic stage of the pandemic it is important to have tools to fight the lingering virus. Two methods are being compared to see if one has a higher efficacy rate than the other. The first consumable pill coming out of the EU reports through 250 trials it has proven successful 247 times. As compared to an UK solution which reports 295 successes from 300 trials.

887.1) What is the null hypothesis if we are testing that the pills are the same? A) PEU = PUK B) PEU ≠ PUK C) PEU ≥PUK D) PEU ≤PUK E) PEU >PUK

887.2) What is the null hypothesis if we are testing that the EU pills are less effective than the

UK pills? A) PEU = PUK B) PEU ≠ PUK C) PEU ≥PUK D) PEU ≤PUK E) PEU <PUK

887.3) What is the null hypothesis if we are testing that the EU pills are more effective than the

UK? A) PEU = PUK B) PEU ≠ PUK C) PEU ≥PUK D) PEU ≤PUK E) PEU >PUK

887.4) What is the alternative hypothesis if we are testing that the EU pills are the same as the

UK pills? A) PEU = PUK B) PEU ≠ PUK C) PEU ≥PUK D) PEU ≤PUK E) PEU >PUK

887.5) What is the alternative hypothesis if we are testing that the EU pills are less effective? A) PEU = PUK B) PEU ≠ PUK C) PEU ≥PUK D) PEU >PUK E) PEU <PUK

887.6) What is the alternative hypothesis if we are testing that the EU pills are more effective? A) PEU = PUK B) PEU ≠ PUK C) PEU ≥PUK D) PEU >PUK E) PEU <PUK

887.7) At a significance level of 0.05 what is the critical value if we are testing that the EU pills

are the same? A) ±1.96 B) ±1.65 C) -1.96 D) + 1.65 E) -1.65

887.8) At a significance level of 0.05 what is the critical value if we are testing that the EU pills

are less effective? A) ±1.96 B) ±1.65 C) -1.96 D) + 1.65 E) -1.65

887.9) At a significance level of 0.05 what is the critical value if we are testing that the EU pills

are more effective? A) ±1.96 B) ±1.65 C) + 1.96 D) + 1.65 E) -1.65

887.10) What is the test statistic and what decision will be made if α = 0.05 and we are testing

that the efficacy rate of the EU pills are the same as the UK pills? A) 0.4551. Reject the null hypothesis and conclude the efficacy rate of the pills are not the same B) 0.4551. Do not reject the null hypothesis and conclude the efficacy rate of the pills are the same C) ±1.96. Do not reject the null hypothesis and conclude the efficacy rate of the pills are not the same D) -±1.96. Reject the null hypothesis and conclude the efficacy rate of the pills are not the same

Answer Key Test name: chapter 10 248) D 249) E 250) B 251) A 252) E 253) C 254) B 255) B 256) B 257) A 258) C 259) E 260) D 261) Section Break 261.1) A 261.2) A 261.3) A 261.4) B 261.5) D 261.6) D 261.7) C 261.8) A 261.9) C 261.10) B 261.11) B 262) Section Break 262.1) E 262.2) C 262.3) B 262.4) B 262.5) C 263) B 264) A 265) B 266) D 267) A 268) B

269) Section Break 269.1) B 269.2) A 269.3) D 269.4) A 269.5) C 269.6) A 269.7) A 269.8) B 269.9) A 269.10) A 269.11) D 270) C 271) A 272) Section Break 272.1) A 272.2) E 272.3) A 272.4) E 272.5) B 273) E 274) B 275) E 276) E 277) A 278) E 279) C 280) E 281) B 282) E 283) D 284) C 285) C 286) A 287) Section Break 287.1) C 287.2) B 288) Section Break 288.1) A 288.2) D

288.3) B 289) Section Break 289.1) D 289.2) C 289.3) A 289.4) B 289.5) A 289.6) D 289.7) C 289.8) C 289.9) D 290) Section Break 290.1) C 290.2) D 290.3) D 290.4) C 290.5) A 290.6) C 290.7) B 291) Section Break 291.1) B 291.2) C 292) Section Break 292.1) A 292.2) B 292.3) E 292.4) A 292.5) A 293) Section Break 293.1) C 293.2) B 293.3) A 293.4) C 294) B 295) C 296) B 297) Section Break 297.1) C 297.2) A 297.3) A

297.4) C 297.5) A 298) Section Break 298.1) E 298.2) A 298.3) C 298.4) C 299) Section Break 299.1) A 299.2) C 299.3) D 299.4) B 299.5) E 299.6) D 299.7) A 299.8) E 299.9) D 299.10) B

Student name:__________ 888)

889)

Which of the following is NOT a characteristic of the F distribution? A) It is based on two sets of degrees of freedom. B) It is positively skewed. C) As the values of X increase, the F curve approaches the X-axis and eventually equals zero. D) It is asymptotic.

i. One characteristic of the F distribution is that F cannot be negative. ii. One characteristic of the F distribution is that computed F can only range between -1 and +1. iii. The shape of the F distribution is positively skewed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

890)

i. One characteristic of the F distribution is that F cannot be negative. ii. The shape of the F distribution is determined by the degrees of freedom for the F-statistic, one for the numerator and one for the denominator. iii. The F distribution's curve is positively skewed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

891)

i. One characteristic of the F distribution is that computed F can only range between -1 and +1. ii. The shape of the F distribution is determined by the degrees of freedom for the F-statistic, one for the numerator and one for the denominator. iii. The F distribution's curve is positively skewed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

892)

i. The F distribution is positively skewed and its values may range from 0 to plus infinity. ii. The F distribution's curve is positively skewed. iii. There is one, unique F distribution for a F-statistic with 29 degrees of freedom in the numerator and 28 degrees of freedom in the denominator. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

893)

i. The shape of the F distribution is determined by the degrees of freedom for the Fstatistic, one for the numerator and one for the denominator. ii. The F distribution's curve is positively skewed. iii. Unlike Student's t distribution, there is only one F distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

894)

i. The F distribution is positively skewed and its values may range from 0 to plus infinity. ii. The F distribution's curve is positively skewed. iii. Like Student's t distribution, a change in the degrees of freedom causes a change in the shape of the F distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

895)

i. The test statistic used in ANOVA is F . ii. The calculated F value must be equal to or greater than zero (0). iii. The shape of the F distribution is symmetrical. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

896)

i. The shape of the F distribution is determined by the degrees of freedom for the Fstatistic, one for the numerator and one for the denominator. ii. Like Student's t distribution, a change in the degrees of freedom causes a change in the shape of the F distribution. iii. The calculated F value must be equal to or greater than zero (0). A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

897)

i. The F distribution is positively skewed and its values may range from 0 to plus infinity. ii. The F distribution's curve is positively symmetrical. iii. Like Student's t distribution, a change in the degrees of freedom causes a change in the shape of the F distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

898)

i. One characteristic of the F distribution is that computed F can only range between -1 and +1. ii. The F distribution's curve is positively skewed. iii. Like Student's t distribution, a change in the degrees of freedom causes a change in the shape of the F distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

899)

i. The test statistic used in ANOVA is t. ii. The calculated F value must be equal to or greater than one (1). iii. The shape of the F distribution is symmetrical. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

900)

What distribution does the F distribution approach as the sample size increases? A) Binomial B) Normal C) Poisson D) Exponential

901)

An F statistic is: A) a ratio of two means. B) a ratio of two variances. C) the difference between three means. D) a population parameter.

902)

Which statement is correct about the F distribution? A) Cannot be negative. B) Cannot be positive. C) Is the same as the t distribution. D) Is the same as the z distribution.

903)

Which of the following are characteristicsofthe F distribution? A) There is a "family" of F distributions. B) The F distribution is continuous. C) The F distribution cannot be negative. D) The F distribution is continuous, cannot be negative, there is a "family" of F distributions.

904)

i. If the computed value of F is 0.99 and the critical value is 3.89, we would not reject the null hypothesis. ii. When comparing two population variances we use the F distribution. iii. A one way ANOVA is used to compare several treatment means. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

905)

Two accounting professors decided to compare the variation of their grading procedures. To accomplish this, they each graded the same 10 exams with the following results Mean Grade

Standard Deviation

Professor 1

79.3

22.4

Professor 2

82.1

12.0

905.1) Using Excel to assist in the comparison, what test would be used? A) ANOVA: Single Factor B) ANOVA: Two-Factor with Replication C) F-Test Two Sample for Variances D) t-Test: Paired Two Sample for Means E) We need the raw data in order to use the F-test in Excel

905.2) What is H0? A) ς21= ς22 B) ς21≠ ς22 C) µ1= µ2 D) µ1≠ µ2

905.3) What is H1? A) ς21= ς22 B) ς21≠ ς22 C) µ1= µ2 D) µ1≠ µ2

905.4) What are the degrees of freedom for the numerator of the F ratio? A) 8 B) 9 C) 10 D) 18 E) 20

905.5) What are the degrees of freedom for the denominator of the F ratio? A) 20 B) 18 C) 10 D) 9 E) 8

905.6) What is the critical value of F at the 0.02 level of significance? A) 5.85 B) 5.35 C) 6.51 D) 4.03

905.7) What is the critical value of F at the 0.10 level of significance? A) 5.85 B) 5.35 C) 3.18 D) 4.03

905.8) The calculated F ratio is: A) 3.484 B) 1.867 C) 3.18 D) 5.35

905.9) At the 1% level of significance, what is the decision? A) Reject the null hypothesis and conclude the variance is different. B) Fail to reject the null hypothesis and conclude the variance is different. C) Reject the null hypothesis and conclude the variance is the same. D) Fail to reject the null hypothesis and conclude the variance is the same.

905.10) At the 5% level of significance, what is the decision? A) Reject the null hypothesis and conclude the variance is different. B) Fail to reject the null hypothesis and conclude no significant difference in the

variance. C) Reject the null hypothesis and conclude the variance is the same. D) Fail to reject the null hypothesis and conclude the variance is the same.

906)

Analysis of variance is used to: A) compare nominal data. B) Compute t test. C) compare population proportion. D) simultaneously compare several population means.

907)

i. The statistical technique used to test the equality of three or more population means is called analysis of variance (ANOVA). ii. To employ ANOVA, the populations should have approximately equal standard deviations. iii. To employ ANOVA, the populations being studied must be approximately normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

908)

i. The statistical technique used to test the equality of three or more population means is called analysis of variance (ANOVA). ii. To employ ANOVA, the populations should have approximately equal standard deviations. iii. The least number of sources of variation in ANOVA is two. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

909)

i. The statistical technique used to test the equality of three or more population means is called analysis of variance (ANOVA). ii. To employ ANOVA, the populations need not have equal standard deviations. iii. To employ ANOVA, the populations being studied must be approximately normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

910)

i. To employ ANOVA, the populations should have approximately equal standard deviations. ii. To employ ANOVA, the populations being studied must be approximately normally distributed. iii. A technique that is efficient when simultaneously comparing more than two population means is known as analysis of variance (ANOVA). A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

911)

i. To employ ANOVA, the populations need not have equal standard deviations. ii. To employ ANOVA, the populations being studied need not be normally distributed. iii. A technique that is efficient when simultaneously comparing more than two population means is known as analysis of deviation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

912)

i. To employ ANOVA, the populations being studied must be approximately normally distributed. ii. A technique that is efficient when simultaneously comparing more than two population means is known as analysis of variance (ANOVA). iii. The least number of sources of variation in ANOVA is two. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

913)

i. To employ ANOVA, the populations should have approximately equal standard deviations. ii. To employ ANOVA, the populations being studied must be approximately normally distributed. iii. The least number of sources of variation in ANOVA is two. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

914)

i. The rejection region for analysis of variance is in the upper tail of the F distribution. ii. In ANOVA, k-1degrees of freedom are associated with the numerator of the F ratio. iii. In ANOVA, k-1degrees of freedom are associated with the denominator of the F ratio. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

915)

Which one of the following is not assumed in the use of ANOVA? A) The populations follow a normal distribution. B) The samples have equal standard deviations. C) The populations have equal standard deviations. D) The populations are independent.

916)

The F test statistic is the ratio of the: A) estimate of the population mean based on the differences among the sample standard deviations to the estimate of the population variance based on the variation within the samples. B) estimate of the population variance based on the differences among the sample means to the estimate of the population variance based on the variation within the samples. C) estimate of the population variance based on the sums of the sample means to the estimate of the population variance based on the variation within the samples.

917)

A random sample of 30 executives from companies with assets over $1 million was selected and asked for their annual income and level of education. The following table summarized the results: SUMMARY Groups

Count

Sum

Average

Variance

High School or less

343

Undergraduate Degree

672

74.66667

234.25

Master’s Degree or More

705

78.33333

242.75

P-value

F crit

10.1846

0.00074

3.443361

ANOVA Source of Variation Between Groups

3872

1936

Within Groups

4182

190.0909

Total

8054

Using this output, what conclusions can you draw? A) Since the calculated F-value is smaller than the F-critical value, there is a significant difference in the incomes of these 3 groups. B) Since the calculated F-value is smaller than the F-critical value, there is no significant difference in the incomes of these three groups. C) Since the P-value is 0.001, there is a 10% chance of these results happening when there is no significant difference in the incomes of these three groups. D) Since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is strong evidence to suggest that the three groups with different levels of education do not all have the same incomes. E) Since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is strong evidence to suggest that all three groups with different levels of education have the same incomes.

918)

A large department store examined a sample of the 18 credit card sales and recorded the amounts charged for each of three types of credit cards: MasterCard, Visa and American Express. Six MasterCard sales, seven Visa and five American Express sales were recorded. The store used ANOVA to test if the mean sales for each credit card were equal. What are the degrees of freedom for the F statistic? A) 18 in the numerator, 3 in the denominator. B) 3 in the numerator, 18 in the denominator. C) 2 in the numerator, 15 in the denominator. D) 0 in the numerator, 15 in the denominator.

919)

In ANOVA, an F statistic is used to test a null hypothesis such as: A) Ho: ς21= ς22= ς23 B) Ho: ς21≠ ς22≠ ς23 C) Ho: µ1= µ2= µ3 D) Ho: µ1≠ µ2≠ µ2

920)

Three different advertisements were used to sell a popular toy. In computing F, how many degrees of freedom are there in the numerator? A) 0 B) 1 C) 2 D) 3

921)

Suppose a package delivery company purchased 14 trucks at the same time. Five trucks were purchased from manufacturer A, four from B and five from manufacturer C. The cost of maintaining each truck was recorded. The company used ANOVA to test if the mean maintenance cost for trucks from each manufacturer were equal. To apply the F test, how many degrees of freedom are in the denominator? A) 2 B) 3 C) 11 D) 14

922)

In an effort to determine the most effective way to teach safety principles to a group of employees, four different methods were tried. Some employees were given programmed instruction booklets and worked through the course at their own pace. Other employees attended lectures. A third group watched a television presentation, and a fourth group was divided into small discussion groups. A high of 10 was possible. Samples of five tests were selected from each group. The test grade results were: Sample Number

Programmed Instruction

Lecture

Group Discussion

922.1) At the 0.01 level, what is the critical value? A) 1.00 B) 1.96 C) 3.24 D) 5.29

922.2) Excel's summary results at the 0.05 level produce the following output: SUMMARY Groups

Count

Sum

Average

Variance

Sample #

2.5

Programmed Instruction

0.5

Lecture

2.5

Group Discussion

1.5

P-value

Fcrit

7.5

0.000734

2.866081

ANOVA Source of Variation Between Groups

13.5

Within Groups

1.8

Total

Using this output, what conclusions can you draw? A) Since the calculated F-value is smaller than the F-critical value, there is a significant difference in the methods of teaching. B) Since the calculated F-value is smaller than the F-critical value, there is no significant difference in the methods of teaching. C) Since the P-value is 0.001, there is a 10% chance of these results happening when there is no significant difference in the methods of teaching. D) Since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is strong evidence to suggest that all teaching methods do not give equal test results. E) Since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is strong evidence to suggest that all teaching methods give equal test results.

922.3) Using Excel to assist in determining if all methods generate the same results, what test

would be used? A) ANOVA: Single Factor. B) ANOVA: Two-Factor with Replication. C) ANOVA: Two-Factor without Replication. D) F-Test Two Sample for Variances. E) t-Test: Paired Two Sample for Means.

923)

Random sample of executives from companies with assets over $1 million was selected and asked for their annual income and level of education. The following MegaStat output summarized the results: One factor ANOVA Mean

Std. Dev

90.44

63.3

9.76

High School or less

90.44

92.6

9.70

Undergraduate Degree

90.44

109.4

31.41

Master’s Degree or More

90.4

27.13

Total

Source

p-value

Treatment

8,452.29

4,226.143

10.09

.0008

Error

9,217.87 22

418.994

Total

17,670.16 24

ANOVA table

923.1) Using this output, what conclusions can you draw? A) The total size of the sample used was 24. B) Since the P-value is 0.0008, there is an 8% chance of these results happening when

there is no significant difference in the incomes of these three groups. C) Since the calculated F-value is large, and the P-value is so small, there is strong evidence to suggest that the three groups with different levels of education do not all have the same incomes. D) Since the calculated F-value is large, and the P-value is so small, there is strong evidence to suggest that all three groups with different levels of education have the same incomes.

923.2) Using this output, what conclusions can be made? A) Since the calculated F-value is smaller than the F-critical value, there is a significant

difference in the incomes of these 3 groups. B) Since the calculated F-value is smaller than the F-critical value, there is no significant difference in the incomes of these three groups. C) Since the P-value is 0.001, there is a 10% chance of these results happening when there is no significant difference in the incomes of these three groups. D) Since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is a strong evidence to suggest that all three groups with different levels of education have the same incomes. E) Since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is a strong evidence to suggest that the three groups with different levels of education do not all have the same incomes.

924)

Suppose that an automobile manufacturer designed a radically new lightweight engine and wants to recommend the grade of gasoline to use. The four grades are: regular, below regular, premium and super premium. The test car made three trial runs on the test track using each of the four grades. Kilometers per liter Regular

Below Regular

Premium

Super Premium

39.31

36.69

38.99

40.04

39.87

40.00

40.02

39.89

39.87

41.01

39.99

39.93

924.1) Assuming any grade can be used at the 0.05 level, what is the critical value of F

using0.05 level of significance? A) 1.96 B) 4.07 C) 2.33 D) 12.00

924.2) Is there a difference in the performance between the four grades of gas? Using the

printout given by Excel, what to you conclude? SUMMARY Groups

Count

Sum

Average

Variance

Regular

119.05

39.68333

0.104533

Below Reg

117.7

39.23333

5.106433

Premium

119

39.66667

0.343633

Super Premium

119.86

39.95333

0.006033

Source of Variation

P-value

Between Groups

0.798025

0.266008

0.191351

0.899368

Within Groups

11.12127

1.390158

Total

11.91929

ANOVA

A) Since the calculated F-value is smaller than the F-critical value, there is a difference

in the performance of these four grades of gas. B) Since the calculated F-value is smaller than the F-critical value, there is no significant difference in the performance of these four grades of gas. C) Since the calculated F-value is larger than the F-critical value, there is no significant difference in the performance in the four grades of gas. D) There is no significant difference in the performance of these four grades of gas as indicated by the calculated F-value being smaller than the F-critical value, and the Pvalue is large at 0.899, there is an 89% chance of these results happening.

924.3) If you were to use Excel to assist in your solution to this problem, which test would you

use? A) B) C) D) E)

ANOVA: Single Factor. ANOVA: Two-Factor with Replication. ANOVA: Two-Factor without Replication. F-Test Two Sample for Variances. t-Test: Paired Two Sample for Means.

925)

The plant manager believes that the temperature in the packaging area of the plant affects the daily rate of production. To investigate, the plant temperature is set at 18 degrees, 20 degrees, and 22 degrees. The number of units produced at each of these temperatures for a sample of days is collected. One factor ANOVA Mean

Std. Dev

8.592592593

5.9

2.89

18 Degrees

8.592592593

11.9

3.82

20 Degrees

8.592592593

8.0

3.00

22 Degrees

8.6

4.03

Total

p-value

7.82

.0024

ANOVA table Source Treatment

166.74

83.370

Error

255.78

10.657

Total

422.52

Using this output, what conclusions can you draw? A) The total size of the sample used was 24. B) Since the P-value is 0.0024, there is a 2% chance of these results happening when there is no significant difference in the number of units produced at the three temperatures. C) Since the calculated F-value is large, and the P-value is so small, there is strong evidence to suggest that the number of units produced at the three temperatures is all the same. D) Since the calculated F-value is large, and the P-value is so small, there is strong evidence to suggest that the number of units produced at the three temperatures is not all the same.

926)

If an ANOVA test is conducted and the null hypothesis is rejected, what does this indicate? A) Too many degrees of freedom. B) No difference between the population means. C) A difference between at least one pair of population means.

927)

Several employees have submitted different methods of assembling a product. Sample data for each method are: Minutes Required for Assembly Sample Number

Lind’s Method Szabo’s Method Carl’s Method Manley’s Method

16.6

22.4

31.4

18.4

17.0

21.5

33.4

19.6

16.9

22.6

30.1

17.6

How many treatments are there? A) 3 B) 4 C) 12 D) 0

928)

An electronics company wants to compare the quality of their cell phones to the cell phones from three competitors. They sample 10 phones from each company and count the number of defects for each phone. If ANOVA is used to compare the average number of defects, the treatments would be defined as: A) the number of cell phones sampled. B) the average number of defects. C) the total number of phones. D) the four companies.

929)

An electronics company wants to compare the quality of their cell phones to the cell phones from three competitors. They sample 10 phones from each company and count the number of defects for each phone. Using Excel, what test is used to compare the average number of defects? A) ANOVA: Single Factor. B) ANOVA: Two-Factor with Replication. C) ANOVA: Two-Factor without Replication. D) F-Test Two Sample for Variances. E) t-Test: Paired Two Sample for Means.

930)

Suppose a package delivery company purchased 14 trucks at the same time. Five trucks were purchased from manufacturer A, four from B and five from manufacturer C. The cost of maintaining each truck was recorded. The company wants to test if the mean maintenance cost for trucks from each manufacturer were equal. Using Excel, what test would be used? A) ANOVA: Single Factor. B) ANOVA: Two-Factor with Replication. C) ANOVA: Two-Factor without Replication. D) F-Test Two Sample for Variances. E) t-Test: Paired Two Sample for Means.

931)

A preliminary study of hourly wages paid to unskilled employees in three metropolitan areas was conducted. Seven employees were included from Area A, 9 from Area B and 12 from Area C. The test statistic was computed to be 4.91. What can we conclude at the 0.05 level? A) Mean hourly wages of unskilled employees all areas are equal. B) Mean hourly wages in at least 2 metropolitan areas are different. C) More degrees of freedom are needed.

932)

Using the Excel printout below to compare the mean annual incomes for executives with Undergraduate and Master's Degree or more, the following statements can be made: SUMMARY Groups

Count

Sum

Average

Variance

Undergraduate Degree

672

74.66667

234.25

Master’s Degree or More

705

78.33333

242.75

Source of Variation

P-value

F crit

Between Groups

60.5

0.253669

0.621367

4.493998

Within Groups

3816

238.5

Total

3876.5

ANOVA

A) since the calculated F-value is smaller than the F-critical value, there is no significant

difference in the incomes of these two groups. B) since the calculated F-value is smaller than the F-critical value, there is a significant difference in the incomes of these two groups. C) since the P-value is 0.62, there is a 62% chance of these results happening when there is no significant difference in the incomes of these two groups. D) since the calculated F-value is larger than the F-critical value, and the P-value is so small, there is strong evidence to suggest that both groups with different levels of education have the same incomes. E) since the calculated F-value is smaller than the F-critical value, there is no significant difference in the incomes of these two groups; also, since the P-value is 0.62, there is a 62% chance of these results happening when there is no significant difference in the incomes of these two groups.

933)

Using the MegaStat printout below to compare the mean annual incomes for executives with Undergraduate and High School or less, the following statements can be made: Hypothesis Test: Independent Groups (t-test, pooled variance) High School or less

Undergraduate Degree

49.00

74.67

mean

7.81

15.31

std. dev.

-25.667

difference (High School or less – Undergraduate Degree)

160.000

pooled variance

12.649

pooled std. dev.

6.375

standard error of difference

Hypothesized difference

-4.03

.0012

p-value (two-tailed)

-39.339

confidence interval 95.% lower

-11.995

confidence interval 95.% upper

13.672

half-width

A) since the 95% confidence interval does not contain the value 0, there is no significant

difference in the incomes of these two groups. B) since the 95% confidence interval does not contain the value 0, there is a significant difference in the incomes of these two groups. C) since the P-value is small, there is a strong chance of these results happening when there is no significant difference in the incomes of these two groups. D) since the P-value is small, there is very little chance of these results happening when there is no significant difference in the incomes of these two groups-therefore those executives with an undergraduate degree make more than their counterparts without.

E) since the 95% confidence interval does not contain the value 0, there is a significant

difference in the incomes of these two groups; also, since the P-value is small, there is very little chance of these results happening when there is no significant difference in the incomes of these two groups.

934)

i. If the computed value of F is 4.01 and the critical value is 2.67, we would conclude that all the population means are equal. ii. Rejecting the null hypothesis in ANOVA indicates that the population means are equal. iii. The null hypothesis for an ANOVA is μ1- μ2≠ μ3. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

935)

i. The alternate hypothesis for ANOVA states that not all the means are equal. ii. For an ANOVA test, rejection of the null hypothesis does not identify which populations differ significantly. iii. If the computed value of F is 4.01 and the critical value is 2.67, we would conclude that all the population means are equal. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

936)

i. For the population means, the alternate hypothesis used in the analysis of variance test states that µ1= µ2= µ3. ii. For an ANOVA test, rejection of the null hypothesis does not identify which populations differ significantly. iii. The null hypothesis for an ANOVA is µ1- µ2= µ3. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

937)

i. For the population means, the alternate hypothesis used in the analysis of variance test states that µ1= µ2= µ3. ii. For an ANOVA test, rejection of the null hypothesis does not identify which populations differ significantly. iii. Not rejecting the null hypothesis in ANOVA indicates that the population means are equal. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

938)

i. If the computed value of F is 4.01 and the critical value is 2.67, we would conclude that all the population means are equal. ii. Not rejecting the null hypothesis in ANOVA indicates that the population means are equal. iii. The null hypothesis for an ANOVA is µ1- µ2= µ3. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

939)

i. For the population means, the alternate hypothesis used in the analysis of variance test states that µ1= µ2= µ3. ii. For an ANOVA test, rejection of the null hypothesis does not identify which populations differ significantly. iii. If the computed value of F is 4.01 and the critical value is 2.67, we would conclude that all the population means are equal. A) (i), (ii), and (iii) are all correct statements. B) (ii) is a correct statement but not (i) or (iii). C) (iii) is a correct statement but not (i) or (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

940)

i. The alternate hypothesis for ANOVA states that not all the means are equal. ii. Not rejecting the null hypothesis in ANOVA indicates that the population means are equal. iii. The null hypothesis for an ANOVA is µ1- µ2= µ3. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

941)

i. For an ANOVA test, rejection of the null hypothesis does not identify which populations differ significantly. ii. Not rejecting the null hypothesis in ANOVA indicates that the population means are equal. iii. The null hypothesis for an ANOVA is µ1- µ2= µ3. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

942)

In a study of low tar cigarettes, five cigarettes from each of three brands were tested to see if the mean amount of tar per cigarette differs among the brands.

942.1) i. The F critical value for alpha = 0.05 is 3.89.

ii. If F calculated is 4.75, the decision if α = 0.05 is to reject H0. iii. If the calculated F is 4.74, the decision if α = 0.01 is to not reject H0. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

942.2) i. The F critical value for alpha = 0.05 is 3.74.

ii. If F calculated is 4.75, the decision if α = 0.05 is to reject H0. iii. If the calculated F is 4.74, the decision if α = 0.01 is to reject H0. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

942.3) i. There are 2 degrees of freedom for the numerator.

ii. There are 14 degrees of freedom for the denominator. iii. If the sum of squares for the brands is 0.07, the mean square for brands is 0.035. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

942.4) i. There are 2 degrees of freedom for the numerator.

ii. There are 12 degrees of freedom for the denominator. iii. If the sum of squares for the brands is 0.07, the mean square for brands is 0.035. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

943)

Given the following Analysis of Variance table for three treatments each with six observations. Source

Sum of Squares

Treatments

1116

Error

1068

Total

2184

Mean Square

What is the decision where α=0.05? A) Reject H0-there is a difference in treatments. B) Fail to reject H0-there is a difference in treatments. C) Reject H0-there is a difference in errors. D) Fail to reject H0-there is a difference in errors.

944)

Suppose we select 20 observations from each of five treatments. The appropriate degrees of freedom are: A) 4 and 95 B) 5 and 20 C) 4 and 19 D) 4 and 20

945)

A manufacturer of automobile transmissions uses three different processes. The management ordered a study of the production costs to see if there is a difference among the three processes. A summary of the findings is shown below. Process 1

Process 2

Process 3

Total

Process Totals ($ 100’s)

137

108

107

352

Sample Size

Sum of Squares

1893

1188

1175

4256

945.1) What is the critical value of F at the 5% level of significance? A) 19.45 B) 3.00 C) 3.35 D) 3.39

945.2) What is the critical value of F at the 1% level of significance? A) 99.46 B) 5.57 C) 5.39 D) 4.61

945.3) What is the sum of squares for the treatment? A) 67.80 B) 58.07 C) 149.34 D) 23.47

945.4) What is the sum of squares of the error? A) 67.80 B) 58.07 C) 149.34 D) 23.47

945.5) What are the degrees of freedom for the numerator of the F ratio? A) 2 B) 3 C) 10 D) 27

945.6) What are the degrees of freedom for the denominator? A) 3 B) 10 C) 27 D) 30

945.7) What are the total degrees of freedom? A) 27 B) 28 C) 29 D) 30

945.8) What is the mean square for treatments? A) 2.511 B) 2.151 C) 33.9 D) 29.035

945.9) What is the mean square for error? A) 2.511 B) 2.151 C) 33.9 D) 29.035

945.10) What is the calculated F? A) 0.086 B) 1.168 C) 11.56 D) 13.50

946)

Given the following Analysis of Variance table for three treatments each with six observations. Source

Sum of Squares

Treatments

1116

Error

1068

Total

2184

Mean Square

946.1) What are the degrees of freedom for the numerator and denominator? A) 3 and 18 B) 2 and 17 C) 3 and 15 D) 2 and 15

946.2) What is the critical value of F at the 5% level of significance? A) 3.29 B) 3.68 C) 3.59 D) 3.20

946.3) What is the mean square for treatments? A) 71.2 B) 71.4 C) 558 D) 534

946.4) What is the computed value of F? A) 7.48 B) 7.84 C) 8.84 D) 8.48

947)

The components of an ANOVA table include: A) sum of squares total. B) mean squares. C) degrees of freedom. D) sum of squares total, mean squares and degrees of freedom are all components of an ANOVA table.

948)

i. If we want to determine which treatment means differ, one method is confidence intervals. ii. If the confidence interval includes 0, there is no difference in the pair of treatment means. iii. If both end points of a confidence interval are of the same sign, it indicates that the treatment means are not different. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

949)

i. If we want to determine which treatment means differ, one method is confidence intervals. ii. If the confidence interval includes 0, there is a difference in the pair of treatment means. iii. If both end points of a confidence interval are of the same sign, it indicates that the treatment means are not different. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) is a correct statement but not (ii) or (iii). E) (i), (ii), and (iii) are all false statements.

950)

A random sample of 30 executives from companies with assets over $1 million was selected and asked for their annual income and level of education. The ANOVA comparing the average income among three levels of education rejected the null hypothesis. The Mean Square Error (MSE) was 243.7. The following table summarized the results: High School or Less

Undergraduate Degree

Master’s Degree or More

Number sampled

Mean salary (1,000s)

76.3

78.3

950.1) When comparing the mean annual incomes for executives with a High School education

or less and Undergraduate Degree, the 95% confidence interval shows an interval of 11.7 to 42.7 for the difference. This result indicates that: A) there is no significant difference between the two incomes. B) the interval contains a difference of zero. C) executives with an Undergraduate Degree earn significantly more than executives with a High School education or less. D) executives with an Undergraduate Degree earn significantly less than executives with a High School education or less.

950.2) When comparing the mean salaries to test for differences between treatment means, the t

statistic is based on: A) the treatment degrees of freedom. B) the total degrees of freedom. C) the error degrees of freedom. D) the ratio of treatment and error degrees of freedom.

950.3) When comparing the mean annual incomes for executives with Undergraduate and

Master's Degree or more, the following 95% confidence interval can be constructed: A) 2.0 ± 2.052 * 6.52 B) 2.0 ± 3.182 * 6.51 C) 2.0 ± 2.052 * 42.46

951)

In ANOVA analysis, when the null hypothesis is rejected, we can find which means are different by: A) constructing confidence intervals. B) adding another treatment. C) doing an additional ANOVA. D) doing a ttest.

952)

If the confidence interval for the difference in treatment means contains zero, then: A) we can conclude that there is a significant difference in the selected treatment means. B) we can conclude that there is no significant difference in the selected treatment means. C) we can conclude that the selected treatment means both equal zero. D) we can conclude that at least one of the selected treatment means equals zero.

953)

The annual dividend rates for a random sample of 16 companies in three different industries, utilities, banking and insurance were recorded. The ANOVA comparing the mean annual dividend rate among three industries rejected the null hypothesis that the dividend rates were equal. The Mean Square Error (MSE) was 3.36. The following table summarized the results: Utilities

Banking

Insurance

Number Sampled

Mean Annual Dividend Rate

11.62

15.4

17.4

953.1) Compare the mean annual dividend rate for companies in the utilities and insurance

industries and construct the 95% confidence interval. A) 5.78 ± 2.160 * 2.40 B) 5.78 ± 2.120 * 2.40 C) 5.78 ± 2.160 * 1.11 D) 5.78 ± 2.120 * 1.11

953.2) The interval is [3.38, 8.18]. Based on the comparison between the mean annual dividend

rate for companies in the utilities and insurance industries: A) a confidence interval shows that the mean annual dividend rates are not significantly different. B) the ANOVA results show that the mean annual dividend rates are significantly different. C) a confidence interval shows that the mean annual dividend rates are significantly different. D) the ANOVA results show that the mean annual dividend rates are not significantly different.

953.3) Based on the comparison between the mean annual dividend rate for companies in

utilities and banking, the 95% confidence interval shows an interval of 1.28 to 6.28 for the difference. This result indicates that: A) there is no significant difference between the two rates. B) the interval contains a difference of 5.00. C) the annual dividend rate in the utilities industry is significantly less than the annual dividend rate in the banking industry. D) the annual dividend rate in the banking industry is significantly less than the annual dividend rate in the utilities industry.

954)

A Marketing team decided to compare the variation in the cost of groceries between a discount store and a club member store. They tracked the grocery purchases of the same family alternating between weeks for 20 separate weeks. Here is what they summarized: Store

Purchases

Mean Cost

Standard Deviation

Discount

n=11

$240.58

$30.15

Club member

n= 9

$285.15

$40.85

954.1) Using Excel to assist in the comparison, what test would be used? A) ANOVA: Single Factor B) ANOVA: Two-Factor with Replication C) F-Test Two Sample for Variances D) We need the raw data in order to use the F-test in Excel E) t-Test: Paired Two Sample for Means

954.2) What is null hypothesis? A) µ1= µ2 B) µ1≠ µ2 C) ς21= ς22 D) ς21≠ ς22

954.3) What is alternative hypothesis? A) ς21= ς22 B) µ1= µ2 C) ς21≠ ς22 D) µ1≠ µ2

954.4) What are the degrees of freedom for the numerator of the F ratio? A) 10 B) 9 C) 8 D) 7

954.5) What are the degrees of freedom for the denominator of the F ratio? A) 7 B) 8 C) 9 D) 10

954.6) What is the critical value of F at the 0.02 level of significance? A) 4.63 B) 4.74 C) 5.06 D) 5.26

954.7) What is the critical value of F at the 0.10 level of significance? A) 3.35 B) 5.81 C) 3.07 D) 2.09

954.8) The calculated F ratio is: A) 0.545 B) 0.738 C) 1.355 D) 1.836

954.9) At the 2% level of significance, what is the decision? A) Reject the null hypothesis and conclude the variance is different. B) Fail to reject the null hypothesis and conclude the variance is different. C) Reject the null hypothesis and conclude the variance is the same. D) Fail to reject the null hypothesis and conclude the variance is the same.

954.10) At the 10% level of significance, what is the decision? A) Reject the null hypothesis and conclude the variance is different. B) Fail to reject the null hypothesis and conclude no significant difference in the

variance. C) Reject the null hypothesis and conclude the variance is the same. D) Fail to reject the null hypothesis and conclude the variance is the same.

955)

A Consumer advocate group is comparing the cost of buying fitness equipment from among 3 choices: 1) in-store 2) online-from store 3) 3rd party web service. A selection of 6 purchases from each method is shown below to determine if the mean purchases are the same. online

3rd party

In Store

by Store

Web service

151

125

130

350

375

360

475

450

425

119

955.1) What is the null hypothesis? A) µ1= µ2 = µ3 B) µ1≠ µ2≠ µ3 2

C) ς 1= ς 2= ς 3 D) ς21≠ ς22≠ ς23

955.2) What is the alternative hypothesis A) The variance prices are not all equal B) The variance prices are all equal C) The mean prices are not all equal D) The mean prices are all equal

955.3) For the F-Critical value, what are the degrees of freedom for both the numerator and the

denominator? A) 3 and 18 B) 2 and 17 C) 3 and 15 D) 2 and 15

955.4) At the 0.05 level of significance what is the F-Critical value? A) 8.70 B) 3.59 C) 3.68 D) 19.4

956)

After running the ANOVA test, if the p-value is 0.995 and the significance level is 0.05: A) We reject the null hypothesis and conclude there is a difference in the cost depending on the method used for the purchase. B) We reject the null hypothesis and conclude there is no difference in the cost depending on the method used for the purchase C) We do not reject the null hypothesis and conclude there is a difference in the cost depending on the method used for the purchase D) We do not reject the null hypothesis and conclude there is no difference in the cost depending on the method used for the purchase

Answer Key Test name: chapter 11 300) C 301) C 302) A 303) D 304) A 305) B 306) A 307) B 308) A 309) C 310) D 311) E 312) B 313) B 314) A 315) D 316) A 317) Section Break 317.1) E 317.2) A 317.3) B 317.4) B 317.5) D 317.6) B 317.7) C 317.8) A 317.9) D 317.10) A 318) D 319) A 320) A 321) C 322) A 323) E 324) A 325) A 326) B

327) B 328) B 329) D 330) C 331) C 332) C 333) C 334) Section Break 334.1) D 334.2) D 334.3) A 335) Section Break 335.1) C 335.2) E 336) Section Break 336.1) B 336.2) D 336.3) A 337) D 338) C 339) B 340) D 341) A 342) A 343) B 344) E 345) E 346) E 347) B 348) D 349) D 350) D 351) B 352) A 353) A 354) Section Break 354.1) A 354.2) C 354.3) C 354.4) A

355) A 356) A 357) Section Break 357.1) D 357.2) B 357.3) B 357.4) A 357.5) A 357.6) C 357.7) C 357.8) D 357.9) A 357.10) C 358) Section Break 358.1) D 358.2) B 358.3) C 358.4) B 359) D 360) B 361) D 362) Section Break 362.1) C 362.2) C 362.3) A 363) A 364) B 365) Section Break 365.1) C 365.2) C 365.3) C 366) Section Break 366.1) D 366.2) C 366.3) C 366.4) C 366.5) D 366.6) C 366.7) C 366.8) D

366.9) B 366.10) D 367) Section Break 367.1) A 367.2) C 367.3) D 367.4) C 368) D

Student name:__________ 957)

i. A scatter diagram is a chart that portrays the relationship between two variables. ii. If a scatter diagram shows very little scatter about a straight line drawn through the plots, it indicates a rather weak relationship. iii. A scatter diagram may be put together using Excel or MegaStat. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

958)

What is the chart called when the paired data (the dependent and independent variables) are plotted? A) Scatter diagram B) Bar C) Pie D) Linear regression

959)

A scatter diagram is a chart, A) in which the dependent variable is scaled along the vertical axis. B) in which the independent variable is scaled along the horizontal axis. C) that portrays the relationship between two variables. D) in which the dependent variable is scaled along the vertical axis, the independent variable is scaled along the horizontal axis and portrays the relationship between two variables.

960)

i. If we are studying the relationship between high school performance and college performance, and want to predict college performance, high school performance is the independent variable. ii. A financial advisor is interested in predicting bond yield based on bond term, i.e., one year, two years, etc. The dependent variable is bond yield. iii. The variable used to predict the value of another is called the independent variable. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

961)

i. If we are studying the relationship between high school performance and college performance, and want to predict college performance, high school performance is the dependent variable. ii. A financial advisor is interested in predicting bond yield based on bond term, i.e., one year, two years, etc. The dependent variable is bond term. iii. The variable used to predict the value of another is called the dependent variable. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

962)

i. If we are studying the relationship between high school performance and college performance, and want to predict college performance, high school performance is the independent variable. ii. An economist is interested in predicting the unemployment rate based on gross domestic product. Since the economist is interested in predicting unemployment, the independent variable is gross domestic product. iii. The variable used to predict the value of another is called the dependent variable. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

963)

What is the variable used to predict the value of another called? A) Independent B) Dependent C) Correlation D) Determination

964)

A sales manager for an advertising agency believes there is a relationship between the number of contacts and the amount of the sales. To verify this belief, the following data was collected: Salesperson

Number of Contacts

Sales (in thousands)

120

110

SUMMARY OUTPUT Regression Statistics Multiple R

0.923254877

R Square

0.852399568

Adjusted R Square

0.844199544

Standard Error

12.63886775

Observations

ANOVA df

F Significance F

Regression

16605.2124 16605.21 103.9509 6.62296E-09

Residual

2875.337604 159.741

Total

Coefficients

19480.55

Standard Error

t Stat

P-value

Lower 95% Upper 95%

Intercept

-7.554392488

7.397798617 -1.02117 0.320704

7.987817705 23.09660268

# contacts

1.983055263

0.194500521 10.19563 6.62E-09 1.574424515 2.391686011

964.1) What is the dependent variable? A) Salesperson B) Number of contacts C) Amount of sales

964.2) What is the independent variable? A) Salesperson B) Number of contacts C) Amount of sales

965)

In the regression equation, Y' = a + bX, what does the letter " a" represent? A) Y intercept B) Slope of the line C) Any value of the independent variable that is selected

966)

In the regression equation, Y' = a + bX, what does the letter " b" represent? A) Y intercept B) Slope of the line C) Any value of the independent variable that is selected D) Value of Y when X= 0

967)

Suppose the least squares regression equation is Y' = 1,202 + 1,133 X. When X = 3, what does Y' equal? A) 5,734 B) 8,000 C) 4,601 D) 4,050

968)

Based on the regression equation, we can A) predict the value of the dependent variable given a value of the independent variable. B) predict the value of the independent variable given a value of the dependent variable. C) measure the association between two variables.

969)

In the equation Y' = a + bX, what is Y'? A) Slope of the line B) Y intercept C) Predicted value of Y, given a specific X value D) Value of Y when X = 0

970)

i. The technique used to measure the strength of the relationship between two sets of variables using the coefficient of correlation and the coefficient of determination is called regression analysis. ii. In order to visualize the form of the regression equation, we can draw a scatter diagram. iii. When a regression line has a zero slope, indicating a lack of a relationship, the line is horizontal to the x-axis. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

971)

i. In order to visualize the form of the regression equation, we can draw a scatter diagram. ii. When a regression line has a zero slope, indicating a lack of a relationship, the line is vertical to the x-axis. iii. In regression analysis, the predicted value of Y' rarely agrees exactly with the actual Y value, i.e., we expect some prediction error. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

972)

i. The least squares technique minimizes the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y. ii. When a regression line has a zero slope, indicating a lack of a relationship, the line is vertical to the x-axis. iii. In regression analysis, the predicted value of Y' rarely agrees exactly with the actual Y value, i.e., we expect some prediction error. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

973)

i. In order to visualize the form of the regression equation, we can draw a scatter diagram. ii. The least squares technique minimizes the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y. iii. In regression analysis, the predicted value of Y' rarely agrees exactly with the actual Y value, i.e., we expect some prediction error. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

974)

i. In order to visualize the form of the regression equation, we can draw a scatter diagram. ii. In regression analysis, the predicted value of Y' rarely agrees exactly with the actual Y value, i.e., we expect some prediction error. iii. The technique used to measure the strength of the relationship between two sets of variables using the coefficient of correlation and the coefficient of determination is called regression analysis. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

975)

976)

i. The technique used to measure the strength of the relationship between two sets of variables using the coefficient of correlation and the coefficient of determination is called regression analysis. ii. In order to visualize the form of the regression equation, we can draw a scatter diagram. iii. The least squares technique minimizes the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

977)

i. The technique used to measure the strength of the relationship between two sets of variables using the coefficient of correlation and the coefficient of determination is called regression analysis. ii. In order to visualize the form of the regression equation, we can draw a scatter diagram. iii. The least squared principle is used to find the best-fitting line because the sum of the squares of the vertical deviations between the actual and estimated values is minimized. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

978)

i. The technique used to measure the strength of the relationship between two sets of variables using the coefficient of correlation and the coefficient of determination is called regression analysis. ii. In order to visualize the form of the regression equation, we can draw a scatter diagram. iii. A regression equation may be determined using a mathematical method called the least squares principle. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

979)

i. The technique used to measure the strength of the relationship between two sets of variables using the coefficient of correlation and the coefficient of determination is called regression analysis. ii. In order to visualize the form of the regression equation, we can draw a scatter diagram. iii. The equation for a straight line going through the plots on a scatter diagram is called a regression equation. It is alternately called an estimating equation and a predicting equation. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

980)

Assume the least squares equation is Y' = 10 + 20 X. What does the value of 10 in the equation indicate? A) Y intercept B) For each unit increased in Y, X increases by 10 C) For each unit increased in X, Y increases by 10

981)

In the least squares equation, Y' = 10 + 20 X the value of 20 indicates A) the Y intercept. B) for each unit increased in X, Y increases by 20. C) for each unit increased in Y, X increases by 20.

982)

Information was collected from employee records to determine whether there is an association between an employee's age and the number or workdays they miss. Excel results are summarized below: SUMMARY OUTPUT Regression Statistics Multiple R

0.525811894

R Square

0.276478148

Adjusted R Square

0.236282489

Standard Error

8.306494901

Observations

ANOVA df

Significance F

Regression

1 474.5885644 474.5886 6.878309 0.017256611

Residual

18 1241.961436 68.99786

Total

Coefficients

1716.55

Standard Error

t Stat

P-value

Lower 95%

Intercept

23.57441118

6.532152996 3.60898 0.002007 9.850856362

Employee Age (years)

-0.452463118

0.172521153 -2.62265 0.017257 -0.8149166891

982.1) From this printout you determine: A) the employee age is the dependent variable. B) the employee age is the independent variable. C) the older the employee the more days they are absent from work. D) the intercept of 23 indicates the most days absent.

982.2) From this printout you determine: A) the employee age is the dependent variable. B) the employee age is the independent variable. C) the regression equation is Y = 23.57 - 0.45x. D) the regression equation is Y = 23.57 x -0.45. E) the employee age is the independent variable; the regression equation is Y = 23.57 -

0.45x.

982.3) From this printout you determine: A) the employee age is the dependent variable. B) the employee age is the independent variable. C) the regression equation is Y = 23.57 - 8.3x. D) the regression equation is Y = 23.57 x - 0.45. E) the employee age is the independent variable; the regression equation is Y = 23.57 +

0.45x.

982.4) From this printout you determine: A) the y-intercept of 23 makes no sense. B) the employee age is the independent variable. C) the regression equation is Y = 23.57 - 0.45x. D) the employee age is the independent variable; the regression equation is Y = 23.57 -

0.45x. E) the employee age is the independent variable; the regression equation is Y = 23.57 0.45x, however the y-intercept of 23 makes no sense.

982.5) From this printout you determine: A) the y-intercept of 23 makes no sense. B) for each additional year of age, we can expect the number of days of absence to

increase by 0.45 days. C) for each additional year of age, we can expect the number of days of absence to decrease by 0.45 days. D) the y-intercept of 23 makes no sense; for each additional year of age, we can expect the number of days of absence to increase by 0.45 days. E) the y-intercept of 23 makes no sense; for each additional year of age, we can expect the number of days of absence to decrease by 0.45 days.

982.6) From this printout you determine: A) When tested at the 2% level of significance, there is a relationship between an

employee's age and the number of days of work absences. B) For each additional year of age, we can expect the number of days of absence to increase by 0.45 days. C) Almost 53% of the variation in the number of absent days can be explained by the variation in the employees ages. D) When tested at the 2% level of significance, there is a relationship between an employee's age and the number of days of work absences; for each additional year of age, we can expect the number of days of absence to increase by 0.45 days.

982.7) From this printout you determine: A) When tested at the 2% level of significance, there is no relationship between an

employee's age and the number of days of work absences. B) For each additional year of age, we can expect the number of days of absence to decrease by 0.2 days. C) Almost 67% of the variation in the number of absent days can be explained by the variation in the employee's ages. D) When tested at the 2% level of significance, there is relationship between an employee's age and the number of days of work absences. For each additional year of age, we can expect the number of days of absence to decrease by 0.45 days. E) When tested at the 2% level of significance, there is no relationship between an employee's age and the number of days of work absences. Almost 67% of the variation in the number of absent days can be explained by the variation in the employee's ages.

983)

Data is collected from 20 salespeople in order to verify that the more contacts made with potential clients, the greater the sales volume. The Excel printout is shown below. SUMMARY OUTPUT Regression Statistics Multiple R

0.923254877

R Square

0.852399568

Adjusted R Square

0.844199544

Standard Error

12.63886775

Observations

ANOVA df

F Significance F

Regression

1 16605.2124 16605.21 103.9509 6.62296E-09

Residual

18 2875.337604 159.741

Total

Coefficients

19480.55

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

-7.554392488 7.397798617 -1.02117 0.320704 -23.09660268 7.987817705

# contacts

1.983055263

0.194500521 10.19563 6.62E-09 1.574424515 2.391686011

983.1) From this printout you determine: A) there is a very weak relationship between the # of contacts and the sales $. B) there is a very strong relationship between the # of contacts and the sales $. C) the regression equation is y = 1.98 x + 7.55. D) the regression equation is y = -7.55 x + 1.98.

983.2) This model predicts that with 25 sales contacts, sales will be in $1000's: A) $49 576. B) $42022. C) $190 843. D) $19 429. E) $16 605.

983.3) The slope in this instance indicates: A) for each additional contact made, the salesperson can anticipate an additional $1983

in sales. B) for each additional contact made, the salesperson can anticipate an additional $1.98 in sales. C) for each additional contact made, the salesperson can anticipate an additional $7,554 in sales. D) for each additional contact made, the salesperson can anticipate a drop of $7,554 in sales. E) for each additional sale made, the salesperson can anticipate an additional 2 contacts are needed.

983.4) The y-intercept in this instance suggests: A) For each additional contact made, the salesperson can anticipate an additional $193 in

sales. B) For each additional contact made, the salesperson can anticipate a drop of $1983 in sales. C) When no contacts are made, the salesperson can anticipate sales of $7554. D) When no contacts are made, the salesperson can anticipate sales of $1983. E) When no contacts are made, the salesperson can anticipate negative sales - therefore the y intercept doesn't make sense for no contacts.

984)

Given the following five points: (-2,0), (-1,0), (0,1), (1,1), and (2,3). What is the slope of the line? A) 0.0 B) 0.5 C) 0.6 D) 0.7

985)

Given the following five points: (-2,0), (-1,0), (0,1), (1,1), and (2,3). What is the Y intercept? A) 0.0 B) 0.7 C) 1.0 D) 1.5

986)

The slope of the regression line: A) represents the average change in Y' for each change of one unit in the independent variable, X. B) represents the average change in X for each change of one unit in the dependent variable, Y. C) represents the change in Y' for each change of one unit in the independent variable, X.

987)

The partial MegaStat output below is regression analysis of the relationship between annual payroll and number of wins in a season for 28 teams in professional sports. The purpose of the analysis is to predict the number of wins when given an annual payroll in $millions. Although technically not a sample, the baseball data below will be treated as a convenience sample of all major league professional sports. Wins

Payroll($mil)

26.914

36.609

27.23

34.568

Adjusted r2

15.718

36.548

Std. Error

39.803

observations

22.949

Predictor variable

27.285

Wins

dependent variable

40.405

35.565

ANOVA table

31.461

Source

35.605

Regression

45.748

Residual

3,626.98

104

38.131

Total

3,988.00

38.303

42.851

8.829

Regression Analysis

Regression output

MS 361.0159

18.197

variables

coefficients

28.855

intercept

68.8291

37.833

payroll

0.3979

14.881

38.35

26.812

24.241

22.615

25.557

103

34.568

987.1) The regression equation is: A) %media:formula2.mml% = 68.8291 + 0.3979 x B) %media:formula2.mml% = 0.3979 + 68.8291 x C) %media:formula2.mml% = 28.2049 + 7.5888 x D) %media:formula2.mml% = 82.5157 + 7.5888 x E) %media:formula2.mml% = 7.5888 + 28.2049 x

987.2) The regression equation is: A) %media:formula3.mml% = 0.379 + 68.8291 x B) %media:formula3.mml% = 68.8291 + 0.3979 x C) %media:formula3.mml% = 0.2473 + 0.3979 x D) %media:formula3.mml% = 68.8291 + 0.2473 x E) %media:formula3.mml% = 0.2473 + 68.8291 x

std. error

0.2473

pvalue

95% upper

0.9063

987.3) Predict the number of wins for a team with PAYROLL = 25(million) (nearest whole

number) A) 10 B) 69 C) 79 D) 74 E) 64

987.4) Predict the number of wins for a team with PAYROLL = 25(million) (nearest whole

number) A) 10 B) 69 C) 79 D) 74 E) 64

987.5) How many independent variables? A) 1 B) 2 C) 9 D) 10 E) 11

987.6) How many degrees of freedom for Residual (Error)? A) 1 B) 2 C) 26 D) 27 E) 28

987.7) The Sum of Squares Regression is: A) 3626.9841 B) 3988.0000 C) 361.0159 D) 68.8291 E) 129.5351

987.8) The critical value of t, at the 5% level of significance, for testing the slope of the

regression line is: A) 2.056. B) 1.706. C) 1.314. D) 1.703. E) 1.061.

987.9) The critical value of t, at the 5% level of significance, for testing the coefficient of

correlation is: A) 1.314. B) 1.706. C) 1.061. D) 1.703. E) 2.056.

988)

Number of Contacts

Sales (in thousands)

120

110

SUMMARY OUTPUT Regression Statistics Multiple R

0.975362147

R Square

0.951331317

Adjusted R Square

0.945247731

Standard Error

9.31044574

Observations

ANOVA df

F Significance F

Regression

13555.4248 13555.42 156.3768 1.56492E-06

Residual

693.475199 86.6844

Total

Coefficients

14248.9

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

-12.20103752

Number of Contacts 2.194641842

6.559575958

-1.86003 0.099925

2.92538154 27.32745659

0.175500178 12.50507 1.56E-06 1.789937443 2.59934624

988.1) What is the Y-intercept of the linear equation? A) -12.201 B) 2.1946 C) -2.1946 D) 12.201

988.2) What is the slope of the linear equation? A) -12.201 B) 12.201 C) 2.1946 D) -2.1946

988.3) The slope in this instance indicates: A) for each additional contact made, the salesperson can anticipate an additional $2195

in sales. B) for each additional contact made, the salesperson can anticipate an additional $2.19 in sales. C) for each additional contact made, the salesperson can anticipate an additional $12,201 in sales. D) for each additional contact made, the salesperson can anticipate a drop of $12,201 in sales. E) for each additional sale made, the salesperson can anticipate an additional 2 contacts are needed.

988.4) What is the regression equation? A) Y' = 2.1946 - 12.201 X B) Y' = -12.201 + 2.1946 X C) Y' = 12.201 + 2.1946 X D) Y' = 2.1946 + 12.201 X

988.5) The y-intercept in this instance suggests: A) For each additional contact made, the salesperson can anticipate an additional $2,195

in sales. B) For each additional contact made, the salesperson can anticipate a drop of $12,201 in sales. C) When no contacts are made, the salesperson can anticipate sales of $12,201. D) When no contacts are made, the salesperson can anticipate negative sales-therefore the y intercept doesn't make sense for no contacts. E) When no contacts are made, the salesperson can anticipate sales of $2,195.

988.6) What is the value of the standard error of estimate? A) 9310.4 B) 8778. C) 8328. D) 8668.

988.7) What is the value of the coefficient of correlation? A) 0.6317 B) 0.9754 C) 0.9513 D) 9.3104

988.8) What is the value of the coefficient of determination? A) 9.3104 B) 0.9754 C) 0.6319 D) 0.9513

988.9) This model predicts that with 25 sales contacts, sales will be: A) $49,576. B) $42,022. C) $302,831. D) $67,067. E) $42,665.

988.10) The 95% prediction interval for a particular person making 30 calls is: A) 55.8, 51.5 B) 51.4, 55.9 C) 46.7, 60.6 D) 31.1, 76.2

988.11) The SS total is: A) 14,249. B) 13,555. C) 693.48. D) 156.37.

988.12) The calculated F value is A) 156.37. B) 02.64. C) 86.68. D) 9.31.

989)

We have collected price per share and dividend information from a sample of 30 companies. Regression Analysis r2 0.658

n 30

r 0.811

Std. Error 3.262 Dep. Var.Dividend ANOVA Source

Regression

p-value

574.1072

1 574.1072

53.94

5.36E-08

Residual

297.9952

28 10.6427

Total

872.1023

Regression output

Confidence interval

Variables

Coefficients

Std.error

t ( df = 28 )

P-value

95% Lower

95% Upper

Intercept

-3.6791

2.0434

-1.800

.0826

-7.8649

0.5068

Price per share

0.2734

0.0372

7.345

5.36E-08

0.1971

0.3496

Predicted values for: Dividend 95% Confidence Interval Price per share

Predicted

lower

95% Prediction Interval upper

lower

upper Leverage

7.25544

5.70640

8.80448

0.39570

14.11518

0.054

989.1) Using the MegaStat printout, determine the regression equation that predicts the dividend

from the stock's selling price. A) Y = 0.27 + 3.68x B) Y = 0.27x + 3.68 C) Y = -3.68 + 0.27x D) Y = -0.27x - 3.68 E) Y=0.27x-3.6791

989.2) The slope in this instance indicates: A) for each additional dollar in stock price, we can anticipate an additional $2.73 in

dividend. B) for each additional dollar in stock price, we can anticipate an additional $3.68 in dividend. C) for each additional dollar in stock price, we can anticipate an additional $0.27 in dividend. D) for each additional dollar in dividend, we can anticipate an additional $2.71 in stock price. E) for each additional dollar in dividend, we can anticipate a drop of $3.68 in stock price.

989.3) The y-intercept in this instance suggests: A) for each additional dollar in stock price, we can anticipate an additional $2.73 in

dividend. B) for each additional dollar in stock price, we can anticipate a drop of $2.41 in dividend. C) when the stock price is zero, we can anticipate a dividend of $0.27. This value, however, makes no sense. D) when the stock price is zero, we can anticipate a dividend of $-3.68. This value, however, makes no sense. E) when the dividends are zero, we can anticipate a negative share price.

989.4) Determine the 95% confidence interval for Dividends when the stock price is $40 per

share: A) B) C) D) E)

990)

$7.26 $5.71, $8.80 $0.40, $14.12 $3.99, $10.52 $7.86, $0.51

i. A coefficient of correlation r close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. ii. The coefficient of determination is the proportion of the total variation in the dependent variable Y that is explained or accounted for by its relationship with the independent variable X. iii. If the coefficient of correlation is -0.90, the coefficient of determination is -0.81. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

991)

Information was collected from employee records to determine whether there is an association between an employee's age and the number or workdays they miss. Partial Excel results are summarized below from two different samples: Regression Statistics sample #1 Multiple R

0.667259023

R Square

0.445234603

Adjusted R Square

0.414414303

Standard Error

2.554642536

Observations

Regression Statistics sample #2 Multiple R

0.525811894

R Square

0.276478148

Adjusted R Square

0.236282489

Standard Error

8.306494901

Observations

Given this information alone, would you decide to continue with the regression analysis for sample #1 or #2 or both? A) Continue with both samples, because the sample sizes are over 15. B) Continue with sample #1 because the multiple r value is larger than that of sample #2. C) Continue with sample #2 because the multiple r value is larger than that of sample #1. D) Don't continue with either sample, because the standard error values are more than 2. E) Don't continue with either sample, because the sample sizes are too small to be of use.

992)

i. The purpose of correlation analysis is to find how strong the relationship is between two variables. ii. A coefficient of correlation of -0.96 indicates a very weak negative correlation. iii. The standard error of estimate measures the accuracy of our prediction. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

993)

i. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. ii. A coefficient of correlation of -0.96 indicates a very weak negative correlation. iii. The coefficient of determination can only be positive. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

994)

i. The strength of the correlation between two variables depends on the sign of the coefficient of correlation. ii. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. iii. Coefficients of -0.91 and + 0.91 have equal strength. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

995)

i. The purpose of correlation analysis is to find how strong the relationship is between two variables. ii. A correlation coefficient of -1 or + 1 indicates perfect correlation. iii. The standard error of estimate measures the accuracy of our prediction. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

996)

i. A correlation coefficient of -1 or +1 indicates perfect correlation. ii. The strength of the correlation between two variables depends on the sign of the coefficient of correlation. iii. If the coefficient of correlation is -0.90, the coefficient of determination is -0.81. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) is a correct statement but not (ii) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

997)

i. A correlation coefficient of -1 or +1 indicates perfect correlation. ii. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. iii. Coefficients of -0.91 and +0.91 have equal strength. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

998)

i. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. ii. If the coefficient of correlation is 0.68, the coefficient of determination is 0.4624. iii. The standard error of estimate measures the accuracy of our prediction. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

999)

i. The strength of the correlation between two variables depends on the sign of the coefficient of correlation. ii. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. iii. The coefficient of determination is found by taking the square root of the coefficient of correlation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) is a correct statement but not (i) or (iii). E) (i), (ii), and (iii) are all false statements.

1000) i. The purpose of correlation analysis is to find how strong the relationship is between

two variables. ii. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between two variables is quite weak. iii. The strength of the correlation between two variables depends on the sign of the coefficient of correlation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1001) What is the difference between a confidence interval and a prediction interval for the

dependent variable in correlation analysis? A) A prediction interval reports the mean value of Y for a given X, whereas a confidence interval reports the range of values of Y for a particular value of X. B) A confidence interval reports the mean value of Y for a given X, whereas a prediction interval reports the range of values of Y for a particular value of X. C) A confidence interval reports the value of Y for a given X, whereas a prediction interval reports the value of Y for a particular value of X.

1002) i. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between

two variables is quite weak. ii. Coefficients of -0.91 and +0.91 have equal strength. iii. If the coefficient of correlation is 0.68, the coefficient of determination is 0.4624. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1003) i. A coefficient of correlation close to 0 (say, 0.08) shows that the relationship between

two variables is quite weak. ii. A coefficient of correlation of -0.96 indicates a very weak negative correlation. iii. If the coefficient of correlation is 0.68, the coefficient of determination is 0.4624. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1004) i. The coefficient of correlation is a measure of the strength of relationship between two

variables. ii. The coefficient of determination can only be positive. iii. The standard error of estimate measures the accuracy of our prediction. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1005) i. Correlation analysis is a group of statistical techniques used to measure the strength of

the relationship (correlation) between two variables. ii. A correlation coefficient of -1 or +1 indicates perfect correlation. iii. The strength of the correlation between two variables depends on the sign of the coefficient of correlation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1006) i. The coefficient of determination is the proportion of the total variation in the dependent

variable Y that is explained or accounted for by its relationship with the independent variable X. ii. The coefficient of determination is found by taking the square root of the coefficient of correlation. iii. The standard error of estimate measures the accuracy of our prediction. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1007) i. The coefficient of determination can only be positive.

ii. If the coefficient of correlation is 0.68, the coefficient of determination is 0.4624. iii. The standard error of estimate measures the accuracy of our prediction. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1008) Which of the following statements regarding the coefficient of correlation is true? A) It ranges from -1.0 to + 1.0 inclusive. B) It measures the strength of the relationship between two variables. C) A value of 0.00 indicates two variables are not related. D) It ranges from -1.0 to + 1.0 inclusive; 0.00 indicates the two variables are not related.

It measures the strength of the relationship between two variables.

1009) What does a coefficient of correlation of 0.70 infer? A) Almost no correlation because 0.70 is close to 1.0. B) 70% of the variation in one variable is explained by the other. C) Coefficient of determination is 0.49. D) Coefficient of non determination is 0.30.

1010) What is the range of values for a coefficient of correlation? A) 0 to +1.0 B) -3 to + 3 inclusive C) -1.0 to +1.0 inclusive D) Unlimited range

1011) i. Perfect correlation means that the scatter diagram will appear as a straight line

ii. If the coefficient of correlation is 0.80, the coefficient of determination is 0.64. iii. The coefficient of determination can assume values between 0% and 100% A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1012) i. If the value of r is -0.96, what does this indicate about the dependent variable as the

independent variable increases? ii. What is the value of the correlation coefficient if there is perfect correlation? iii. If the dependent variable is measured in dollars, in what units is the standard error of estimate measured? A) it increases; zero; dollars squared B) it decreases; +/-1.0; dollars squared C) it increases; 1.0; dollars ($) D) it decreases; +/-1.0; dollars ($) E) it decreases; zero; dollars

1013) i. If the coefficient of correlation is 0.80, what is the coefficient of determination?

ii. What is a measure of the scatter of observed values around the regression line called? iii. If the correlation between sales and advertising is + 0.6, what percent of the variation in sales can be attributed to advertising? A) 0.4; standard deviation; 0.3. B) 0.64; standard error of the estimate; 36%. C) 0.64; standard error of the estimate; 60%. D) 0.08; variation; 36%. E) 0.4; standard error of the estimate; 60%.

1014) i. If the coefficient of correlation is -0.81, what is the coefficient of determination?

ii. If the value of r is -0.96, what does this indicate about the dependent variable as the independent variable increases? iii. If the correlation between sales and advertising is +0.6, what percent of the variation in sales can be attributed to advertising? A) 0.6561; it decreases;36%. B) 0.6561; it increases;36%. C) 0.6561; it decreases;60%. D) 0.9; it decreases;6%. E) 0.9; it increases;60%.

1015) i. If the coefficient of determination is 0.81, what is the coefficient of correlation?

ii. If the coefficient of correlation is -0.81, what is the coefficient of determination? iii. If the dependent variable is measured in dollars, in what units is the standard error of estimate measured? A) +/-0.9; 0.6561; dollars squared. B) +/-0.9; 0.6561; dollars. C) 0.6561; 0.9; dollars. D) 0.6561; +/-0.9; dollars squared. E) 0.9; -0.9; dollars squared.

1016) i. What is the range of values that the coefficient of determination can assume?

ii. What is a measure of the scatter of observed values around the regression line called? iii. If the correlation between sales and advertising is +0.6, what percent of the variation in sales can be attributed to advertising? A) 0% to 1%; standard variation;36%. B) both positive and negative values; standard deviation;6%. C) 0% to 100%; standard error of the estimate; 36%. D) 0% to 100%; standard variation;36%. E) both positive and negative values; standard error of the estimate; 36%.

1017) i. If the coefficient of correlation is 0.70, what is the coefficient of determination?

ii. If the value of r is -0.88, what does this indicate about the dependent variable as the independent variable increases? iii. If the dependent variable is measured in hours, in what units is the standard error of estimate measured? A) 0.49; it decreases; hours. B) 0.49; it decreases; hours squared. C) 0.49; it increases; hours. D) 0.8367; it decreases; hours. E) 0.8367; it increases; hours squared.

1018) i. If there is absolutely no relationship between two variables, what will Pearson's r

equal? ii. If the value of r is -0.96, what does this indicate about the dependent variable as the independent variable increases? iii. What is the value of the correlation coefficient if there is perfect correlation? A) one (1); decreases; zero (0). B) one (1); increases; zero (0). C) zero (0); decreases; +/-1.0. D) zero (0); increases; +/-1.0. E) +/-1.0; nothing; +/-1.0.

1019) i. If the coefficient of correlation is 0.70, what is the coefficient of determination?

ii. If the value of r is -0.88, what does this indicate about the dependent variable as the independent variable increases? iii. If the correlation between sales and advertising is -0.7, what percent of the variation in sales can be attributed to advertising? A) 0.49; it decreases;0.49. B) 0.49; it decreases;0.7. C) 0.49; it increases;0.49. D) 0.8367; it decreases;0.7. E) 0.8367; it increases;0.8367.

1020) i. If there is absolutely no relationship between two variables, what will Pearson's r

equal? ii. If the coefficient of correlation is 0.80, what is the coefficient of determination? iii. If the coefficient of determination is 0.81, what is the coefficient of correlation? A) zero (0); 0.64; 0.9 or -0.9. B) zero (0); 0.64; 0.09. C) one (1); 0.64; 0.6561. D) one (1); 0.64; 0.9 or -0.9. E) zero (0); 0.8944; 0.6561.

1021) If the correlation between two variables is close to one, the association is A) strong. B) moderate. C) weak. D) none.

1022) If the correlation coefficient between two variables equals zero, what can be said of the

variables X and Y? A) Not related B) Dependent on each other C) Highly related

1023) What can we conclude if the coefficient of determination is 0.94? A) Strength of relationship is 0.94. B) Direction of relationship is positive. C) 94% of total variation in one variable is explained by variation in the other variable.

1024) What does it indicate if r = -1.00? A) Dependent variable can be perfectly predicted by the independent variable. B) All of the variation in the dependent variable can be accounted for by the independent

variable. C) High values of one variable are associated with high values of the other variable. D) Coefficient of determination is 0%. E) Coefficient of determination is 100%. High values of one variable are associated with low values of the other variable. All of the variation in the dependent variable can be accounted for by the independent variable. Dependent variable can be perfectly predicted by the independent variable.

1025) If r = 0.65, what does the coefficient of determination equal? A) 0.194 B) 0.423 C) 0.577 D) 0.806

1026) What does the coefficient of determination equal if r = 0.89? A) 0.94 B) 0.89 C) 0.79 D) 0.06

1027) Which value of r indicates a stronger correlation than 0.40? A) -0.30 B) -0.50 C) + 0.38 D) 0

1028) Which value of r indicates a stronger correlation than -0.40? A) -0.30 B) -0.50 C) 0 D) 0.30

1029) Which value of r indicates a stronger correlation than 0.25? A) -0.30 B) -0.50 C) 0.30 D) -0.30, -0.50, 0.30 E) 0.15, 0.30

1030) Which value of r indicates a stronger correlation than 0.55? A) -0.30 B) -0.50 C) 0.30 D) .05 E) -0.65

1031) What is the range of values for the coefficient of determination? A) -1 to +1 inclusive B) -100% to + 100% inclusive C) -100% to 0% inclusive D) 0% to 100% inclusive

1032) If all the plots on a scatter diagram lie on a straight line, what is the standard error of

estimate? A) -1 B) +1 C) 0 D) Infinity

1033) What is the measure that indicates how precise a prediction of Y is based on X or,

conversely, how inaccurate the prediction might be? A) Regression equation B) Slope of the line C) Standard error of estimate

1034) Which of the following is true about the standard error of estimate? A) Measure of the accuracy of the prediction. B) Based on squared vertical deviations between Y and Y'. C) Cannot be positive. D) All of these statements are correct. Measure of the accuracy of the prediction; based

on squared vertical deviations between Y and Y'; cannot be negative.

1035) Information was collected from employee records to determine whether there is an

association between an employee's age and the number or workdays they miss. Partial Excel results are summarized below: SUMMARY OUTPUT Regression Statistics Multiple R

0.525811894

R Square

0.276478148

Adjusted R Square

0.236282489

Standard Error

8.306494901

Observations

Given this information alone, would you decide to continue with the regression analysis? A) Yes, because the information is based on a significant size sample. B) Yes, because the multiple r value is large. C) No, because the multiple r value is small. D) No, because the standard error value is more than 5. E) Yes, because the standard error value is more than 5.

1036) In correlation analysis, the independent variable is A) the variable that is scaled on the vertical axes. B) the variable that is being predicted or estimated. C) a variable that provides the basis for estimation. It is the predictor variable.

1037) In correlation analysis, the dependent variable is A) the variable that is scaled on the horizontal axes. B) the variable that is being predicted or estimated. C) a variable that provides the basis for estimation. It is the predictor variable.

1038) If the decision in the hypothesis test of the population correlation coefficient is to reject

the null hypothesis, what can we conclude about the correlation in the population? A) It is zero. B) It could be zero. C) It is not zero. D) It equals the computed sample correlation.

1039) i. The basic question in testing the significance of rho is to see if there is zero correlation

in the population from which the sample was selected. ii. A t test is used to test the significance of the coefficient of correlation. iii. When testing the strength of the relationship between two variables, the alternate hypothesis is: H0: ρ ≠ 0. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1040) The following table shows the number of workdays absent based on the length of

employment in years. Number of Workdays Absent

Length of Employment (in yrs)

1040.1) i. The Y intercept of the linear equation is 7.7407.

ii. The dependent variable (Y) is the number of years employed. iii. The slope of the linear equation is -0.6852. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1040.2) i. The independent variable (X) is the number of years employed.

ii. The dependent variable (Y) is the number of work days absent. iii. The slope of the linear equation is -0.6852. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1040.3) i. The Y intercept of the linear equation is 7.7407.

1040.4) i. The Y intercept of the linear equation is 7.7407.

ii. The dependent variable (Y) is the number of work days absent. iii. The slope of the linear equation is -0.6852 A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1040.5) i. The Y intercept of the linear equation is 4.407.

1040.6) i. The least squares equation for the data: Y' = 7.107 - 0.6852X.

1040.7) i. The least squares equation for the data: Y' = 7.7407 - 0.6852X.

ii. The dependent variable (Y) is the number of work days absent. iii. The negative slope indicates an inverse relationship between the variables. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1040.8) What is the standard error of estimate? A) 7.7107 B) -0.6852 C) +0.6852 D) 1.31515 E) 3.11

1041) Determine the linear regression equation. Regression Analysis r2

0.746

-0.864

Std. Error

1.315 Dep. Var.

Number of Workdays Absent

ANOVA table Source

P-value

14.66

.0123

Regression

25.3519

1 25.3519

Residual

8.6481

5 1.7296

Total

34.0000

Regression output

Confidence interval

Variables

Coefficient s

Std. error

t ( df=5 )

P=value

95% lower

95% upper

Intercept

7.7407

0.8715

8.882

.0003

5.504

9.9811

Length of Employment (years)

-0.6852

0.1790

-3.828

.0123

-1.1452

-0.2251

A) B) C) D)

Y' = 7.7107 - 0.6852 X Y' = 7.7407 - 0.6852 X Y' = 7.7407 + 0.6852 X Y' = -7.7407 - 0.6852 X

1042) Predict the number of days absent when an employee has 6 years of employment. Regression Analysis r2

0.746

-0.864

Std. Error

1.315 Dep. Var.

Number of Workdays Absent

ANOVA table Source

P-value

14.66

.0123

Regression

25.3519

1 25.3519

Residual

8.6481

5 1.7296

Total

34.0000

Regression output

Confidence interval

Variables

Coefficient s

Std. error

t ( df=5 )

P=value

95% lower

95% upper

Intercept

7.7407

0.8715

8.882

.0003

5.504

9.9811

Length of Employment (years)

-0.6852

0.1790

-3.828

.0123

-1.1452

-0.2251

A) B) C) D)

3.63 6.33 3.36 6.36

1043) i. The basic question in testing the significance of rho is to see if there is zero correlation

in the population from which the sample was selected. ii. A t test is used to test the significance of the coefficient of correlation. iii. Suppose a sample of 15 homes recently sold in your area is obtained. The correlation between the area of the home, in square feet, and the selling price is 0.40. We want to test the hypothesis that the correlation in the population is zero versus the alternate that it is greater than zero. You determine that the rejection region should fall in the lower tail if this is a onetailed test and we use a 0.01 significance level. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1044) Given the following five points: (-2,0), (-1,0), (0,1), (1,1), and (2,3).

If the regression equation is Y' = 2 - 0.4 X, what is the value of Y' when X = -3? A) 0.8 B) 3.2 C) -10.0 D) 14.0

1045) The correlation between two variables is -0.63 for a sample of 20 observations. What is

the computed value of the test statistic? A) 3.442 B) -0.63 C) -3.442 D) -1.26

1046) The correlation between two variables is -0.63 for a sample of 20 observations. Which of

the following is a correct conclusion based on the data given? Use the.05 significance level. A) Reject H0. There is a negative association between the variables. B) Do not reject H0. There is a negative association between the variables. C) Reject H0. There is a positive association between the variables.

1047) The correlation between two variables is 0.29 for a sample of 12 observations. Based on a

null hypothesis of no correlation versus an alternative hypothesis of positive correlation, what conclusion may be drawn at the.05 level of significance? A) Reject H0. There is evidence of positive correlation between the variables. B) Do not reject H0. We do not have evidence of positive correlation. C) Reject H0. We have evidence of negative correlation.

1048) i. The basic question in testing the significance of rho is to see if there is zero correlation

in the population from which the sample was selected. ii. A z test is used to test the significance of the coefficient of correlation. iii. Perfect correlation means that the scatter diagram will appear as a straight line. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1049) i. A t test is used to test the significance of the coefficient of correlation.

ii. When testing the strength of the relationship between two variables, the alternate hypothesis is: H0: ρ ≠ 0. iii. Suppose a sample of 15 homes recently sold in your area is obtained. The correlation between the area of the home, in square feet, and the selling price is 0.40. We want to test the hypothesis that the correlation in the population is zero versus the alternate that it is greater than zero. You determine that the rejection region should fall in the lower tail if this is a onetailed test and we use a 0.01 significance level. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1050) i. A t test is used to test the significance of the coefficient of correlation.

ii. When testing the strength of the relationship between two variables, the alternate hypothesis is: H0: ρ > 0. iii. Perfect correlation means that the scatter diagram will appear as a straight line A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1051) Given the following five points: (-2,0), (-1,0), (0,1), (1,1), and (2,3).

What is the standard error of the estimate? A) 0 B) 0.135 C) 0.367 D) 0.606

1052) i. Trying to predict weekly sales with a standard error of estimate of $1,955, we would

conclude that 68 percent of the predictions would not be off more than $1,955, 95 percent would not be off by more $3,910, and 99.7 percent would not be off by more than $5,865. ii. The smaller the sample, the smaller the possible error as measured by the standard error of estimate. iii. Approximately 95% of the values lie within two standard errors of the regression line. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1053) i. The smaller the sample, the smaller the possible error as measured by the standard error

of estimate. ii. Approximately 68% of the values lie within two standard errors of the regression line. iii. For a set of observations, there is no difference in the width of a confidence interval and the width of a predictor interval. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements

1054) i. Trying to predict weekly sales with a standard error of estimate of $1,955, we would

conclude that 68 percent of the predictions would not be off more than $1,955, 95 percent would not be off by more $3,910, and 99.7 percent would not be off by more than $5,865. ii. Approximately 68% of the values lie within one standard error of the regression line. iii. For a set of observations, there is no difference in the width of a confidence interval and the width of a predictor interval. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1055) i. Trying to predict weekly sales with a standard error of estimate of $1,955, we would

conclude that 68 percent of the predictions would not be off more than $1,955, 95 percent would not be off by more $3,910, and 99.7 percent would not be off by more than $5,865. ii. A confidence interval can be determined for the mean value of Y for a given value of X. iii. Approximately 95% of the values lie within two standard errors of the regression line. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1056) i. Trying to predict weekly sales with a standard error of estimate of $1,955, we would

conclude that 68 percent of the predictions would not be off more than $1,955, 95 percent would not be off by more $3,910, and 99.7 percent would not be off by more than $5,865. ii. Approximately 95% of the values lie within two standard errors of the regression line. iii. The smaller the sample, the smaller the possible error as measured by the standard error of estimate. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1057) The difference between formulas for constructing a confidence interval and a prediction

interval is A) the prediction interval is the square root of the confidence interval. B) the addition of "1" to the quantity under the radical sign. 2 C) the prediction interval uses r and the confidence interval uses r. D) no difference.

1058) Which of the following is NOT a difference between a confidence interval and a

prediction interval? A) Addition of "1" under the radical for the prediction interval. B) Confidence interval uses the standard error of estimate and the prediction interval does not. C) Prediction interval refers to a specific case. D) Confidence interval is narrower than the prediction interval.

1059) When comparing the 95% confidence and prediction intervals for a given regression

analysis, A) the confidence interval is wider than a prediction interval. B) the confidence interval is narrower than a prediction interval. C) there is no difference between confidence and prediction intervals. D) the sample size determines the difference.

1060) Data is collected from 20 salespeople in order to verify that the more contacts made with

potential clients, the greater the sales volume. The MegaStat printout is shown below. (or use the Excel file #contacts and sales n = 20 data only) Salesperson

# Contacts

Sales ($000)

120

110

r2 0.852

n 20

r 0.923

Std. Error 12.639

Dep. Var. Sales ($000)

Source

Regression Residual

Regression Analysis

ANOVA table MS

p-value

16,605.2124

1 16,605.2124

103.95

6.62E-09

2,875.3376

18 159.7410

Total

19,480.5500

Regression output

Confidence interval

Variables

Coefficients

Std.error

t ( df=18 )

P-value

95% Lower

95% Upper

Intercept

-7.5544

7.3978

-1.021

.3207

-23.0966

7.9878

# contacts

1.9831

0.1945

10.196

6.62E-09

1.5744

2.3917

Predicted values for: Sales ($000) 95% Confidence Interval # contacts

Predicted

lower

95% Prediction Interval upper

lower

upper Leverage

42.022

34.779

49.265

14.499

69.545

1060.1) Determine the 95% prediction interval for Sales when 25 contacts are made. A) $14,499, $69,545 B) $14.499, $49.265 C) $34,779, $49,265 D) $34.78, 449.27 E) $14.50, $69.55

1060.2) Determine the 95% confidence interval for Sales when 25 contacts are made. A) $14,499, $69,545 B) $14.499, $49.265 C) $34,779, $49,265 D) $34.78, $449.27 E) $14.50, $69.55

0.074

1060.3) Analyzing this printout, we can determine: A) the value of t indicates that the coefficient of correlation is greater than zero when

using the 0.05 level of significance. B) the value of t indicates that the coefficient of correlation is greater than zero when using the 0.01 level of significance. C) the value of t indicates that the coefficient of correlation cannot be shown to be different than zero when tested at the 0.01 level of significance. D) the standard error indicates that the coefficient of correlation is not different from zero. E) the value of t indicates that the coefficient of correlation is greater than zero at both the 0.01 and 0.05 levels of significance.

1060.4) Analyzing this printout we can determine: A) the value of t indicates that the coefficient of correlation is greater than zero when

using the 0.05 level of significance. B) the value of t indicates that the coefficient of correlation is greater than zero when using the 0.01 level of significance. C) the p-value indicates that the coefficient of correlation is greater than zero when tested at the 0.01 level of significance. D) for each extra contact made, sales can be anticipated at approximately $1,113. E) the value of t indicates that the coefficient of correlation is greater than zero at both the 0.05 and 0.01 levels of significance. The p-value indicates that the coefficient of correlation is greater than zero when tested at the 0.01 level of significance. For each extra contact made, sales can be anticipated at approximately $1,983.

1061) The partial MegaStat output below is regression analysis of the relationship between

attendance and number of wins in a season for a sample of 11 teams in professional sports. The purpose of the analysis is to predict annual attendance (000) when given the number of wins . Wins Attend(000)

Regression Analysis

2841

2035

2085

Adjusted r2

2417

2245

Std. Error

2654

observations

1688

predictor variable

2581

Attend.

dependent variable

1873

2453

ANOVA table

3138

Source

Regression

p-value

1130353 13.81

Residual

736467

Total

1866821

Regression output

Confidence interval

variables

coefficients

intercept

82.5157

Wins

28.2049

Std. error

7.5888

pvalue

95% lower

95% upper

Refer to the printout above. The Sum of Squares Regression is: A) 1,866,821 B) 736,467 C) 1,130,353 D) 82.5157 E) 28.2049

1062) Given the following five points: (-2,0), (-1,0), (0,1), (1,1), and (2,3).

What is the critical value necessary to determine a confidence interval for a 95% level of confidence? A) 2.132 B) 2.353 C) 2.776 D) 3.182

1063) Given the following five points: (-2,0), (-1,0), (0,1), (1,1), and (2,3).

What is the critical value necessary to determine a confidence interval for a 90% level of confidence? A) 1.533 B) 1.638 C) 2.132 D) 2.353

1064) A sales manager for an advertising agency believes there is a relationship between the

number of contacts and the amount of the sales. To verify this belief, the following data was collected: Salesperson

Number of Contacts

Sales (in thousands)

120

110

r2 0.951

n 10

r 0.975

Regression Analysis

Std. Error 9.310 Dep. Var. Sales ($000) ANOVA table Source

p-value

1 13,555.4248

156.38

1.56E-06

Regression

13,555.4248

Residual

693,4752

Total

14,248.9000

86.6844

Regression output

Confidence interval

Variables

Coefficients

Std.error

t ( df=8 )

P-value

95% Lower

95% Upper

Intercept

-12.2010

6.5596

-1.860

.0999

-27.3274

2.9254

# contacts

2.1946

0.1755

12.505

1.56E-06

1.7899

2.5993

Predicted values for: Sales ($000) 95% Confidence Interval # contacts

Predicted

lower

95% Prediction Interval upper

lower

upper Leverage

53.638

46.711

60.566

The 95% confidence interval for 30 calls is: A) 55.8, 51.5. B) 51.4, 55.9. C) 46.7, 60.6. D) 31.1, 76.2.

1065) A regression analysis yields the following information:

Y' = 2.24 + 1.49 X Syx = 1.66; ∑x = 32; ∑x2 = 134; n = 10 Estimate the value of Y' when X = 4. A) 10.45 B) 3.73 C) 8.20 D) Cannot be computed

1066) A regression analysis yields the following information:

Y' = 2.24 + 1.49 X Syx = 1.66; ∑x = 32; ∑x2 = 134; n = 10 Compute the 95% confidence interval when X = 4. A) 0.0, 4.05 B) 4.15, 12.25 C) 2.67, 5.33 D) 6.87, 9.53

31.078

76.198

0.104

1067) What is the standard error of the estimate? Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

A) B) C) D)

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

136.8552 12323.56 11.6985 Cannot be computed

1068) What is the coefficient of determination? Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

A) B) C) D)

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

91.8% 8.2% 90.0% Cannot be computed

1069) What is the correlation coefficient? Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

A) B) C) D)

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

0.81 0.958 -0.84 0.006

1070) Using a 5% significance level, what is the critical value for the F-statistic? Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

A) B) C) D)

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

5.32 239 3.23 241

1071) The regression equation is: Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

A) Y' = 2.179463 - 12.8094 X B) Y' = -12.8094 + 2.179463X C) 12.8094 X = 2.179463 Y'

1072) The regression analysis can be summarized as follows: Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

A) B) C) D)

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

No significant relationship between the variables. A significant negative relationship exists between the variables. A significant positive relationship exists between the variables. For every unit increase in X, Y decreases by 12.8094.

1073) If testing the hypothesis: H0: ρ = 0, the computed t - statistic is: Coefficients Constant

-12.8094

Independent Variable

2.179463

ANOVA df

A) B) C) D)

F 90.04814

SSR

12323.56

SSE

1094.842

136.8552

SS Total

13418.4

9.45. 8.84. 8.18. Cannot be computed.

1074) The relationship between interest rates as a percent ( X) and housing starts ( Y) is given

by the linear equation Y' = 4094 - 269 X.

1074.1) What will be the number of housing starts if the interest rate is 8.25%? A) 1875 B) 1785 C) 4094 D) 3825

1074.2) What will be the number of housing starts if the interest rate rose to 16%? A) 1875 B) 1785 C) -4094 D) Zero, since you can't have negative housing starts.

1074.3) At what interest rate will there be no permits for housing starts? A) 8.26% B) 15.22% C) 14.32% D) 16.61%

1074.4) What happens to housing starts as interest rates fall? A) Housing starts remain the same. B) Housing starts rise. C) Housing starts fall. D) Unable to determine from the information given.

1074.5) What happens to housing starts as interest rates fall? For what interest rate will the

maximum number of housing starts be achieved? A) Housing starts remain the same; 0% B) Housing starts rise; 0% C) Housing starts fall; 10% D) Housing starts rise; 15%

1075) High school students were interested in a teacher's claim that the longer the length of time

(hours) that a student studies for a test, the higher the test score. The students collected the data and the teacher did the regression analysis with the following results ANOVA df

Regression

1199.900

Residual

1725.700

Total

9 Coefficients

Standard Error

Intercept

46.024

11.641

Time

2.134

0.905

1075.1) If a student studies 10 hours, what is the predicted score? A) 63.6 B) 66.3 C) 76.4 D) 67.4

1075.2) Determine the linear regression equation. A) Y = 46.024 + 2.134X B) Y = 2.134 + 46.024X C) Y = 11.641 + 46.024X D) Y = 2.134X - 46.024

t-Stat

1076) During the fourth phase of the pandemic a randomly chosen day was selected to correlate

the 10 highest countries number of Covid-19 cases (in millions) with the total number of deaths (in 10 thousands). ANOVA df

Regression

4769.00

Residual

793.00

Total

9 Coefficients

Standard Error

Intercept

3.41

4.69

Cases (M)

1.58

0.23

1076.1) Determine the linear regression equation. A) Y'= 1.58+3.41 X B) Y'= 3.41+4.69 X C) Y'= 3.41+1.58 X D) Y'= 3.41+0.23 X

1076.2) What is the value of the standard error of the overall regression model? A) 99.125 B) 9.96 C) 4.69 D) 0.23

1076.3) What is the overall accuracy of the regression equation? A) 99.125 B) 69.96 C) 4.69 D) 0.23

t-Stat

1076.4) What is the degree of freedom of the numerator? A) 0 B) 1 C) 2 D) 8 E) 9

1076.5) What is the degree of freedom of the denominator? A) 0 B) 1 C) 2 D) 8 E) 9

1076.6) What is the null hypothesis if we want to determine whether there is a positive relation

between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.7) What is the null hypothesis if we want to determine whether there is a direct relation

between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.8) What is the null hypothesis if we want to determine whether there is a negative relation

between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.9) What is the null hypothesis if we want to determine whether there is a relation between

the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.10)

What is the null hypothesis if we want to determine whether there is an inverse relation between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.11)

What is the alternative hypothesis if we want to determine whether there is a positive relation between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.12)

What is the alternative hypothesis if we want to determine whether there is a direct relation between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.13)

What is the alternative hypothesis if we want to determine whether there is an indirect relation between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ < 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.14)

What is the alternative hypothesis if we want to determine whether there is a negative relation between the number of cases and the number of deaths? A) H1: ρ > 0 B) H1: ρ ≤ 0 C) H1: ρ < 0 D) H1: ρ ≠ 0 E) H1: ρ = 0

1076.15)

What is the alternative hypothesis if we want to determine whether there is a relation between the number of cases and the number of deaths? A) H0: ρ > 0 B) H0: ρ ≤ 0 C) H0: ρ ≥ 0 D) H0: ρ ≠ 0 E) H0: ρ = 0

1076.16)

What is the t critical value if the significance level is 0.05 and we are testing whether there is a direct relationship between the total number of cases and the total number of deaths? A) 1.397 B) 1.860 C) 2.306 D) 2.896 E) 3.355

1076.17)

What is the t critical value if the significance level is 0.05 and we are testing whether there is a postive relationship between the total number of cases and the total number of deaths? A) 1.397 B) 1.860 C) 2.306 D) 2.896 E) 3.355

1076.18)

What is the t critical value if the significance level is 0.05 and we are testing whether there is a relationship between the total number of cases and the total number of deaths? A) 1.397 B) 1.860 C) 2.306 D) 2.896 E) 3.355

1076.19)

What is the t critical value if the significance level is 0.10 and we are testing whether there is a direct relationship between the total number of cases and the total number of deaths? A) 1.397 B) 1.860 C) 2.306 D) 2.896 E) 3.355

1076.20)

What is the t critical value if the significance level is 0.10 and we are testing whether there is a relationship between the total number of cases and the total number of deaths? A) 1.397 B) 1.860 C) 2.306 D) 2.896 E) 3.355

1076.21) A) B) C) D)

Compute the value of the test statistic. 1.58 1.860 3.09 6.87

1076.22)

What % of the variation in the number of deaths can be explained by the variation in the number of cases? A) -0.86 B) 0.86 C) -.93 D) 0.93

1076.23) A) B) C) D)

1076.24)

What is the coeffiecient of determination? -0.86 0.86 -.93 0.93

What type and how strong is the relation between number of cases and number of

deaths? A) B) C) D)

Negative -0.86 Positive 0.86 Negative -.93 Positive 0.93

1076.25) A) B) C) D)

Compute the coefficient of correlation. -0.86 0.86 -.93 0.93

1076.26) A) B) C) D)

What is the correlation between Deaths and Cases? -0.86 0.86 -.93 0.93

1076.27)

Using the regression equation, if a country has a total of 1 million cases what is the predicted number of deaths? Multiply your answer by 10,000. A) 49,900 B) 113,100 C) 160,500 D) 192,100

1076.28)

Using the regression equation, if a country has a total of 5 million cases what is the predicted number of deaths? Multiply your answer by 10,000. A) 49,900 B) 113,100 C) 160,500 D) 192,100

1076.29)

Using the regression equation, if a country has a total of 8 million cases what is the predicted number of deaths? Multiply your answer by 10,000. A) 49,900 B) 113,100 C) 160,500 D) 192,100

1076.30)

Using the regression equation, if a country has a total of 10 million cases what is the predicted number of deaths? Multiply your answer by 10,000. A) 49,900 B) 113,100 C) 160,500 D) 192,100

1076.31)

Based on the output calculate the t statistic. What decision would you make at the 0.05 significance level whether there is a positive relation between the number of cases and the number of deaths? A) 1.86. Do not Reject Ho in favour of H1. Therefore there is a not positive relation between the number of cases and the number of deaths. B) 1.50. Because the t critical value is larger than the t statistic value, do not reject that there is a relationship between the number of cases and the number of deaths. C) 1.86. There is a relation but we don't know if it is a direct relation. D) 6.87. Since the t statistic is larger than the t critical value, reject the null hypothesis and conclude there is a positive relation between the number of cases and the number of deaths.

Answer Key Test name: chapter 12 369) C 370) A 371) D 372) A 373) E 374) B 375) A 376) Section Break 376.1) C 376.2) B 377) A 378) B 379) C 380) A 381) C 382) D 383) C 384) C 385) A 386) B 387) D 388) D 389) A 390) A 391) A 392) A 393) B 394) Section Break 394.1) B 394.2) E 394.3) B 394.4) E 394.5) E 394.6) A 394.7) D 395) Section Break 395.1) B

395.2) B 395.3) A 395.4) E 396) D 397) C 398) A 399) Section Break 399.1) A 399.2) B 399.3) C 399.4) C 399.5) A 399.6) C 399.7) C 399.8) A 399.9) E 400) Section Break 400.1) A 400.2) C 400.3) A 400.4) B 400.5) D 400.6) A 400.7) B 400.8) D 400.9) E 400.10) D 400.11) A 400.12) A 401) Section Break 401.1) E 401.2) C 401.3) D 401.4) B 402) B 403) B 404) C 405) C 406) D 407) A

408) 409) 410) 411) 412) 413) 414) 415) 416) 417) 418) 419) 420) 421) 422) 423) 424) 425) 426) 427) 428) 429) 430) 431) 432) 433) 434) 435) 436) 437) 438) 439) 440) 441) 442) 443) 444) 445) 446) 447)

C A A D B B A C A B C A D C C A D B A B C A C A A A A C E B C B B D E D C C D C

448) C 449) B 450) C 451) A 452) Section Break 452.1) A 452.2) C 452.3) A 452.4) C 452.5) A 452.6) D 452.7) A 452.8) A 453) B 454) A 455) B 456) B 457) C 458) A 459) B 460) C 461) B 462) C 463) D 464) C 465) E 466) B 467) A 468) B 469) B 470) B 471) B 472) Section Break 472.1) A 472.2) C 472.3) E 472.4) E 473) C 474) D 475) D

476) C 477) C 478) D 479) C 480) A 481) B 482) A 483) B 484) C 485) A 486) Section Break 486.1) A 486.2) D 486.3) B 486.4) B 486.5) B 487) Section Break 487.1) D 487.2) A 488) Section Break 488.1) C 488.2) B 488.3) B 488.4) B 488.5) D 488.6) B 488.7) B 488.8) C 488.9) E 488.10) C 488.11) A 488.12) A 488.13) C 488.14) C 488.15) D 488.16) B 488.17) B 488.18) C 488.19) A 488.20) B

488.21) D 488.22) B 488.23) B 488.24) D 488.25) D 488.26) D 488.27) A 488.28) B 488.29) C 488.30) D 488.31) D

Student name:__________ 1077) i. Multiple regression is used when two or more independent variables are used to predict

a value of a single dependent variable. ii. The values of b1, b2, and b3 in a multiple regression equation are called the net regression coefficients. They indicate the change in the predicted value for a unit change in one X when the other X variables are held constant. iii. Multiple regression analysis examines the relationship of several dependent variables on the independent variable. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1078) A manager at a local bank analyzed the relationship between monthly salary and three

independent variables: length of service (measured in months), gender (0 = female, 1 = male) and job type (0 = clerical, 1 = technical). The following ANOVA summarizes the regression results: ANOVA df

F 5.96

Regression

1004346.771

334782.257

Residual

1461134.596

56197.48445

Total

2465481.367

Coefficients

Standard Error

t Stat

P-value

Intercept

784.92

322.25

2.44

0.02

Service

9.19

3.20

2.87

0.01

Gender

222.78

89.00

2.50

0.02

Job

-28.21

89.61

-0.31

0.76

1078.1) In the regression model, which of the following are dummy variables? A) Intercept B) Service C) Service and gender D) Gender and job E) Service, gender, and job

1078.2) Based on the ANOVA, the multiple coefficient of determination is A) 5.957%. B) 59.3%. C) 40.7%. D) cannot be computed.

1078.3) Based on the ANOVA and a 0.05 significance level, the global null hypothesis test of the

multiple regression model. A) will be rejected and conclude that monthly salary is related to all of the independent variables. B) will be rejected and conclude that monthly salary is related to at least one of the independent variables. C) will not be rejected. D) will show a high multiple coefficient of determination.

1078.4) Based on the hypothesis tests for the individual regression coefficients, A) all the regression coefficients are not equal to zero. B) "job" is the only significant variable in the model. C) only months of service and gender are significantly related to monthly salary. D) "service" is the only significant variable in the model.

1078.5) The results for the variable gender show that, A) males average $222.78 more than females in monthly salary. B) females average $222.78 more than males in monthly salary. C) gender is not related to monthly salary. D) gender and months of service are correlated.

1079) The information below is from the multiple regression analysis computer output for 28

teams in Major League Baseball. The model is designed to predict wins using attendance, payroll, batting average, home runs, stolen bases, errors and team ERA. Regression Analysis R2 Adjusted R2 R Std. Error 28

Observations

Predictor variables

Wins is the dependent variable ANOVA table Source

Regression

3,588.9368

p-value

Std. error

pvalue

95%lower

95%upper

Residual Total

3,988.0000

Regression output

Confidence interval

Variables

Coefficients

intercept

-70.3279

Attendance

0.2960

1.2165

.8102

-2.2416

2.8336

Payroll

-0.2072

0.1301

.1268

-0.4786

0.0641

Batg, Avg

840.3707

112.9908

3.5E07

604.6761

1,076.0652

Home Runs

0.1199

0.0423

.0103

0.0316

0.2081

Stolen Bases

0.0591

0.0254

.0305

0.0062

0.1120

Errors

-0.1719

0.0492

.0023

-0.2744

-0.0693

Team ERA

-16.3315

1.8966

1079.1) Predict the number of wins for a team with:

BATAVG = 0.260 HOMERUNS = 150 ERA = 3 STOLENBASE = 100 ERROR = 100 PAYROLL = 25(million) ATTENDANCE = 3(million) A) 77 B) 102 C) 187 D) 210 E) 186

1079.2) The multiple correlation coefficient is: A) 0.900 B) 0.930 C) 0.656 D) 0.867 E) 0.949

1079.3) The standard error of estimate is: A) 4.467 B) 5.698 C) 5.864 D) 19.977 E) 15.917

3.6E08

-20.2877

-12.3753

1079.4) The number of degrees of freedom to be used in determining the critical value of t to be

used in a hypothesis test of the regression coefficients is: A) 27 B) 26 C) 22 D) 21 E) 20

1079.5) The critical value of F to be used in the global test of the model is: (5% level of

significance) A) 2.51 B) 2.58 C) 3.70 D) 5.57 E) 3.39

1079.6) The computed F for the global test is: A) 7.802 B) 25.695 C) 15.790 D) 26.981 E) 114.779

1079.7) The t-value computed for testing the coefficient "Batg. Avg." is: A) 112.991. B) 2.086. C) 7.438. D) 2.832. E) -1.593.

1080) Angela Chou has been asked to investigate the determinants of poverty in Ontario

communities. She collected data on 60 communities from Statistics Canada. She selected the percentage of poor persons living under the poverty line [Poor (%)], measured by Low Income Cut-Off, designed by Statistics Canada as a measure of poverty for a community, as the dependent variable. The independent variables selected are percent of single families in each community, the unemployment rate in each community, percent of population in the community holding a bachelor's degree as their highest level of education attained and percent of population holding a High School Diploma as their highest level of education attained. Given the regression equation Poor (%) = -3.81 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) - 0.170 Bachelor's Degree (%) - 0.003 High School (%).

1080.1) How many dependent variables are there in this regression? A) 1 B) 2 C) 3 D) 4 E) 5

1080.2) Interpret the numbers 3.81 and 0.798. A) As the % of Single Families in an Ontario community increases, the % of poor

families increase as well, with a maximum of 3.81% of the population being poor. B) As the % of Single Families in an Ontario community increases, the % of poor families decrease. C) There are 3.81% poor families and 0.798 Single-Families in Ontario communities. D) 3.81 is the y-intercept. When all of the dependent variables have a value of zero, we can expect that 3.81% of the community to be poor. 0.789 indicates that for an extra 0.789% of poor families in a community, we can expect that the % of single families will increase by 1%. E) When all of the independent variables have a value of zero, we can expect that 3.81% of the community to be poor, i.e. 0%. The 0.798 indicates that for each extra % of single families in a community, we can expect that the % poor will increase by almost 0.8%.

1080.3) What is the estimated percentage of poor persons living below the poverty line in a

community with 5% of the community as single-families, a 5% unemployment rate, only 5% holding a Bachelor's Degree and 25% having High School as their highest attained educational level? A) 2.375 B) -2.375 C) 11.845 D) -11.845

1080.4) Which single event would have the strongest effect in reducing the % poor in Ontario? A) Decreasing the % of single families by 5%. B) Decreasing the Unemployment rate by 5%. C) Increasing the % of persons with a Bachelor's Degree by 10%. D) Decreasing the % of persons with a High School Diploma by 40%. E) Increasing the % of persons with a Bachelor's Degree by 15%.

1081) The following correlations were computed as part of a multiple regression analysis that

used education, job and age to predict income. Income

Education

Job

Income

1.000

Education

0.677

1.000

Job

0.173

-0.181

1.000

Age

0.369

0.073

0.689

1081.1) Which is the dependent variable? A) Income B) Age C) Education D) Job

Age

1.000

1081.2) Which independent variable has the strongest association with the dependent variable? A) Income B) Age C) Education D) Job

1081.3) Which independent variable has the weakest association with the dependent variable? A) Income B) Age C) Education D) Job

1081.4) What is this table called? A) Net regression coefficients B) Coefficients of nondetermination C) Analysis of variance D) Correlation matrix

1082) i. The values of b1, b2 and b3 in a multiple regression equation are called the net

regression coefficients. They indicate the change in the predicted value for a unit change in one X when the other X variables are held constant. ii. Multiple regression analysis examines the relationship of several dependent variables on the independent variable. iii. A multiple regression equation defines the relationship between the dependent variable and the independent variables in the form of an equation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1083) i. Multiple regression analysis examines the relationship of several dependent variables

on the independent variable. ii. A multiple regression equation defines the relationship between the dependent variable and the independent variables in the form of an equation. iii. Autocorrelation often happens when data has been collected over periods of time. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1084) i. A multiple regression equation defines the relationship between the dependent variable

and the independent variables in the form of an equation. ii. Autocorrelation often happens when data has been collected over periods of time. iii. Homoscedasticity occurs when the variance of the residuals (Y - Y') is different for different values of Y'. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1085) i. Autocorrelation often happens when data has been collected over periods of time.

ii. Homoscedasticity occurs when the variance of the residuals (Y - Y') is different for different values of Y'. iii. Violating the need for successive observations of the dependent variable to be uncorrelated is called autocorrelation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1086) i. Violating the need for successive observations of the dependent variable to be

uncorrelated is called autocorrelation. ii. If an inverse relationship exists between the dependent variable and independent variables, the regression coefficients for the independent variables are negative. iii. Given a multiple linear equation Y' = 5.1 + 2.2 X1 - 3.5 X2, assuming other things are held constant, an increase in one unit of the second independent variable will cause a -3.5 unit change in Y. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1087) i. If an inverse relationship exists between the dependent variable and independent

variables, the regression coefficients for the independent variables are positive. ii. Given a multiple linear equation Y' = 5.1 + 2.2 X1 - 3.5 X2, assuming other things are held constant, an increase of one unit in the second independent variable will cause a -3.5 unit change in Y. iii. When the variance of the differences between the actual and the predicted values of the dependent variable are approximately the same, the variables are said to exhibit homoscedasticity. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1088) i. Multiple regression is used when two or more independent variables are used to predict

a value of a single dependent variable. ii. The values of b1, b2 and b3in a multiple regression equation are called the net regression coefficients. They indicate the change in the predicted value for a unit change in one X when the other X variables are held constant. iii. Autocorrelation often happens when data has been collected over periods of time. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1089) i. The values of b1, b2 and b3in a multiple regression equation are called the net regression

coefficients. They indicate the change in the predicted value for a unit change in one X when the other X variables are held constant. ii. A multiple regression equation defines the relationship between the dependent variable and the independent variables in the form of an equation. iii. If an inverse relationship exists between the dependent variable and independent variables, the regression coefficients for the independent variables are positive. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1090) Multiple regression analysis is applied when analyzing the relationship between A) an independent variable and several dependent variables. B) a dependent variable and several independent variables. C) several dependent variables and several independent variables. D) several regression equations and a single sample.

1091) Angela Chou has been asked to investigate the determinants of poverty in Ontario

0.8924

R Square

0.7963

Adjusted R Square

0.7815

Standard Error

2.1671

Observations

ANOVA df

F Significance F

Regression

1009.84

252.46

Residual

55 258.3095132 4.6965366

Total

53.75 2.27236E-18

1268.15

Coefficients

Standard Error

t Stat

Pvalue

Lower 95% Upper 95%

Intercept

-3.8073

3.0436

-1.2510

0.2162

-9.9068

2.2921

Single-Fam (%)

0.7976

0.0950

8.3924

0.0000

0.6071

0.9880

Unemp. Rate (%)

0.6241

0.1237

5.0461

0.0000

0.3762

0.8719

Batch. Degree (%)

-0.1702

0.0846

-2.0111

0.0492

-0.3398

-0.0006

High Sch. (%)

-0.0034

0.1195

-0.0287

0.9772

-0.2429

0.2360

1091.1) Determine the regression equation. A) Poor (%) = -3.81 - 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) -

0.170 Bachelor's Degree (%) - 0.003 High School (%) B) Poor (%) = -3.81 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) + 0.170 Bachelor's Degree (%) + 0.003 High School (%) C) Poor (%) = 3.81 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) 0.170 Bachelor's Degree (%) - 0.003 High School (%) D) Poor (%) = -3.81 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) 0.170 Bachelor's Degree (%) - 0.003 High School (%) E) Poor (%) = 3.81 + 0.798 Single-Families (%) - 0.624 Unemployment Rate (%) + 0.170 Bachelor's Degree (%) - 0.003 High School (%)

1091.2) Determine the regression equation. A) Poor (%) = -3.81 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) -

0.170 Bachelor's Degree (%) - 0.0034 High School (%) B) Poor (%) = -3.88 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) 0.170 Bachelor's Degree (%) - 0.0034 High School (%) C) Poor (%) = 3.88 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) 0.170 Bachelor's Degree (%) - 0.0034 High School (%) D) Poor (%) = -3.88 - 0.798 Single-Families (%) - 0.624 Unemployment Rate (%) 0.170 Bachelor's Degree (%) - 0.0034 High School (%) E) Poor (%) = 3.88 + 0.798 Single-Families (%) + 0.624 Unemployment Rate (%) + 0.170 Bachelor's Degree (%) - 0.0034 High School (%)

1091.3) Using the output, determine which variable Angela should consider deleting. A) It doesn't matter which she uses, the results are virtually the same in any case. B) Angela should delete the high school information, because the P-value is over 0.05. C) Angela should delete the bachelor's degree information, because the P-value is close

to 0.05. D) Angela should delete the unemployment rate information because the P-value is 0.00. E) Angela should exclude the single-family and unemployment information because the P-value values are 0.

1092) How is the Y intercept in the multiple regression equation represented? A) b1 B) x1 C) b2 D) x2 E) a

1093) If there are four independent variables in a multiple regression equation, there are also

four A) B) C) D)

Y-intercepts. regression coefficients. dependent variables. constant terms.

1094) For a unit change in the first independent variable with other things being held constant,

what change can be expected in the dependent variable in the multiple regression equation Y' = 5.2 + 6.3 X1- 7.1 X2? A) -7.1 B) +6.3 C) +5.2 D) +4.4

1095) If the correlation between two variables X and Y, is +0.67, what is the regression

coefficient for these two variables? A) +0.67 B) > 0 C) < 0 D) = 0

1096) A sample of General Mills employees was studied to determine their degree of

satisfaction with their present life. A special index, called the index of satisfaction was used to measure satisfaction. Six factors were studied: age at the time of first marriage (X1), annual income (X2), number of children living (X3), value of all assets (X4), status of health in the form of an index (X5) and the average number of social activities per week (X6). Suppose the multiple regression equation is: Y' = 16.24 + 0.017X1 + 0.00028X2 +42X3 + 0.0012X4 + 0.09X5 + 26.8X6.

1096.1) Explain the meaning of b2. A) For each additional$1,000 of annual income, their satisfaction index is expected to

increase by 0.28 points. B) For each additional$1,000 of annual income, their satisfaction index is expected to increase by 2.8 points. C) For each additional$1,000 of annual income, their satisfaction index is expected to increase by 28 points. D) For each additional living child, their satisfaction index is expected to increase by 42 points. E) For each additional living child, their satisfaction index is expected to increase by 4.2 points.

1096.2) Explain the meaning of b3. A) For each additional living child, their satisfaction index is expected to increase by 4.2

points. B) For each additional living child, their satisfaction index is expected to increase by 42 points. C) For each additional living child, their satisfaction index is expected to increase by 0.42 points. D) For each additional$1,000 of annual income, their satisfaction index is expected to increase by 0.028 points. E) For each additional$1,000 of annual income, their satisfaction index is expected to increase by 2.8 points.

1096.3) Explain the meaning of b4. A) For each additional living child, their satisfaction index is expected to increase by 42

points. B) For each additional$1,000 of annual income, their satisfaction index is expected to increase by 0.028 points. C) For each additional$10,000 in assets, their satisfaction index is expected to increase by 0.12 points. D) For each additional$10,000 in assets, their satisfaction index is expected to increase by 1.2 points. E) For each additional$10,000 in assets, their satisfaction index is expected to increase by 12 points.

1096.4) Explain the meaning of b5. A) For each additional10 points on the health status index, their satisfaction index is

expected to increase by 9 points. B) For each additional10 points on the health status index, their satisfaction index is expected to increase by 0.09 points. C) For each additional10 points on the health status index, their satisfaction index is expected to increase by 0.9 points. D) For each additional10 points on the health status index, their satisfaction index is expected to drop by 0.09 points. E) For each additional10 points on the health status index, their satisfaction index is expected to decrease by 9 points.

1096.5) Explain the meaning of b6. A) For each additional social activity per week, their satisfaction index is expected to

increase by 26.8 points. B) For each additional social activity per week, their satisfaction index is expected to increase by 2.68 points. C) For each additional10 points on the health status index, their satisfaction index is expected to increase by 0.9 points. D) For each additional$10,000 in assets, their satisfaction index is expected to increase by 12 points. E) For each additional living child, their satisfaction index is expected to increase by 42 points.

1096.6) What is the estimated index of satisfaction for a person who first married at 25, has an

annual income of $26,500, has two children, has assets of $156,000, has in index of health status of 141, and has 2.5 social activities per week? A) 389.1 B) 421.6 C) 366.0 D) 601.6 E) 769.8

1096.7) What is the estimated index of satisfaction for a person who first married at 25, has an

annual income of $46,000, has two children, has assets of $200,000, has in index of health status of 141, and has 2.5 social activities per week? A) 368.3 B) 433.2 C) 366.0 D) 601.6 E) 769.8

1096.8) What is the estimated index of satisfaction for a person who first married at 25, has an

annual income of $46,000, has two children, has assets of $350,000, has in index of health status of 141, and has 2.5 social activities per week? A) 368.3 B) 421.6 C) 366.0 D) 627.3 E) 769.8

1096.9) What is the estimated index of satisfaction for a person who first married at 25, has an

annual income of $60,000, has two children, has assets of $350,000, has in index of health status of 141, and has 2 social activities per week? A) 777.70 B) 796.60 C) 603.76 D) 601.60 E) 769.80

1096.10)

What is the estimated index of satisfaction for a person who first married at 25, has an annual income of $100,000, has two children, has assets of $500,000, has in index of health status of 141, and has 2 social activities per week? A) 777.7 B) 796.6 C) 588.6 D) 601.6 E) 809.1

1096.11)

What is the estimated index of satisfaction for a person who first married at 25, has an annual income of $100,000, has two children, has assets of $500,000, has in index of health status of 141, and has 3 social activities per week? A) 777.7 B) 835.9 C) 588.6 D) 601.6 E) 769.8

1096.12)

What is the estimated index of satisfaction for a person who first married at 25, has an annual income of $100,000, has two children, has assets of $500,000, has in index of health status of 141, and has 3.5 social activities per week? A) 777.7 B) 796.6 C) 849.3 D) 601.6 E) 769.8

1097) What are the degrees of freedom associated with the regression sum of squares? A) Number of independent variables B) 1 C) F-ratio D) (n -k-1)

1098) In a regression analysis, three independent variables are used in the equation based on a

sample of forty observations. What are the degrees of freedom associated with the Fstatistic? A) 3 and 39 B) 4 and 40 C) 3 and 36 D) 2 and 39

1099) In regression analysis, the dfreg = ________. A) the sample size - 1 B) the sample size - k-1 C) the number of dependent variables D) the number of independent variables E) the sample size -k

1100) In regression analysis, the dferr = ________. A) the sample size -1 B) the sample size - k-1 C) the number of dependent variables D) the number of independent variables E) the sample size -k

1101) What does the multiple standard error of estimate measure? A) Change in Y' for a change in X1. B) Variation of the data points between Y and Y'. C) Variation due to the relationship between the dependent and independent variables. D) Amount of explained variation.

1102) If a multiple regression analysis is based on ten independent variables collected from a

sample of 125 observations, what will be the value of the denominator in the calculation of the multiple standard error of estimate? A) 125 B) 10 C) 114 D) 115

1103) i. Multiple R2 measures the proportion of explained variation.

ii. 90% of total variation in the dependent variable is explained by the independent variable for a multiple R2 = 0.90. iii. The multiple standard error of estimate measures the variation about the regression plane when two independent variables are considered. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1104) i. 90% of total variation in the dependent variable is explained by the independent

variable for a multiple R2= 0.90. ii. The multiple standard error of estimate measures the variation about the regression plane when two independent variables are considered. iii. The multiple coefficient of determination, R2, reports the proportion of the variation in Y that is not explained by the variation in the set of independent variables. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1105) i. The standard error of estimate measures the variation about the regression plane when

two independent variables are considered. ii. The multiple coefficient of determination R2, reports the proportion of the variation in Y that is not explained by the variation in the set of independent variables. iii. The coefficient of multiple determination reports the strength of the association between the dependent variable and the set of independent variables. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i) is true but (ii) and (iii) are false statements.

1106) i. The coefficient of multiple correlation reports the strength of the association between

the dependent variable and the set of independent variables. ii. The standard error of estimate for two independent variables measures the variation about a regression plane. iii. A multiple coefficient of determination equaling -0.76 is definitely possible. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1107) i. The multiple standard error of estimate for two independent variables measures the

variation about a regression plane. ii. A multiple coefficient of determination equaling -0.76 is definitely possible. iii. Multiple R2 measures the proportion of explained variation relative to total variation. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1108) i. A coefficient of multiple determination equaling -0.76 is definitely possible.

ii. Multiple R2 measures the proportion of explained variation relative to total variation. iii. The number of degrees of freedom associated with the regression sum of squares in the regression equation model equals the number of independent variables. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1109) i. The multiple standard error of estimate measures the variation about the regression

plane when two independent variables are considered. ii. A coefficient of multiple determination equaling -0.76 is definitely possible. iii. The number of degrees of freedom associated with the regression sum of squares in the regression equation model equals the number of independent variables. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1110) i. The multiple coefficient of determination R2, reports the proportion of the variation in

Y that is explained by the variation in the set of independent variables. ii. The coefficient of multiple correlation reports the strength of the association between the dependent variable and the set of independent variables. iii. A coefficient of multiple determination equaling -0.76 is definitely possible. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1111) How is the percentage of variation explained between the set of independent variables

and the dependent variable measured? A) Confidence intervals B) Autocorrelation C) Coefficient of multiple determination D) Standard error of estimate

1112) What is the measurement of explained variation? A) Coefficient of multiple determination B) Coefficient of multiple nondetermination C) Regression coefficient D) Correlation matrix

1113) If the coefficient of multiple determinations is 0.81, what percent of variation is not

explained? A) 19% B) 90% C) 66% D) 81%

1114) What is the range of values for R-Squared? A) -100% to -100% inclusive B) -100% to 0% inclusive C) 0% to +100% inclusive D) Unlimited range

1115) The coefficient of determination measures the proportion of A) explained variation relative to total variation. B) variation due to the relationship among variables. C) error variation relative to total variation. D) variation due to regression.

1116) What happens as the scatter of data values about the regression plane increases? A) Standard error of estimate increases. B) R2 decreases. C) (1 -R2) decreases. D) Residual sum of squares decreases. E) (1 -R2), residual sum of squares and standard error of estimate all increase, and R2

decreases.

1117) Which test statistic do we apply to test the null hypothesis that the multiple regression

coefficients are all zero? A) z B) t C) F D) SPSS-X

1118) What test investigates whether all the independent variables have zero net regression

coefficients? A) Multicollinearity B) Autocorrelation C) Global D) Pearson

1119) Which of the following is a characteristic of the F-distribution? A) Normally distributed B) Positively skewed C) Negatively skewed D) Equal to the t-distribution

1120) The best example of a null hypothesis for a global test of a multiple regression model is: A) H0: β1 = β2 = β3 = β4=0. B) H0: μ1 = μ2 = μ3 = μ4. C) H0: β1 = 0. D) If F is greater than 20.00 then reject.

1121) The best example of an alternate hypothesis for a global test of a multiple regression

model is: A) H1: β1 = β2 = β3 = β4. B) H1: β1 ≠ β2 ≠ β3 ≠ β4. C) H1: Not all the β's are 0. D) if F is less than 20.00 then fail to reject.

1122) In multiple regression, a dummy variable can be included in a multiple regression model

as A) B) C) D)

an additional quantitative variable. a nominal variable with three or more values. a nominal variable with only two values. a new regression coefficient.

1123) i. If the null hypothesis β4 = 0 is not rejected, then the independent variable X4 has a

strong effect in predicting the dependent variable. ii. A dummy variable is added to the regression equation to control for error. iii. A variable whose possible outcomes are coded as a "1" or a "0" is called a strong independent variable. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1124) i. A variable whose possible outcomes are coded as a "1" or a "0" is called a dummy

variable. ii. A dummy variable is added to the regression equation to control for error. iii. If the null hypothesis β4 = 0 is not rejected, then the independent variable X4 has no effect in predicting the dependent variable. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1125) i. A variable whose possible outcomes are coded as a "1" or a "0" is called a dummy

variable. ii. If the null hypothesis β4 = 0 is not rejected, then the independent variable X4 has no effect in predicting the dependent variable. iii. A dummy variable is added to the regression equation to control for error. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1126) What can we conclude if the net regression coefficients in the population are not

significantly different from zero? A) Strong relationship exists among the variables. B) No relationship exists between the dependent variable and the independent variables. C) Independent variables are good predictors. D) Good forecasts are possible.

1127) Hypotheses concerning individual regression coefficients are tested using which statistic? A) t-statistic B) z-statistic C) χ2(chi-square statistic) D) H

1128) The best example of a null hypothesis for testing an individual regression coefficient is: A) H0: β1 = β2 = β3 = β4. B) H0: μ1 = μ2 = μ3 = μ4. C) H0: β1 = 0. D) if F is greater than 20.00 then reject.

1129) Angela Chou has been asked to investigate the determinants of poverty in Ontario

communities. She collected data on 60 communities from Statistics Canada. She selected the percentage of poor persons living under the poverty line [Poor (%)], measured by Low Income Cut-Off, and designed by Statistics Canada as a measure of poverty for a community, as the dependent variable. The independent variables selected are percent of single families in each community, the unemployment rate in each community, percent of population in the community holding a bachelor's degree as their highest level of education attained, and percent of population holding a High School Diploma as their highest level of education attained. Using the outputs below for this data set, determine whether Angela should use the model with the high school data included, or the data without the high school data, and why. SUMMARY OUTPUT (no high school data) Regression Statistics Multiple R

0.8924

R Square

0.7963

Adjusted R Square

0.7854

Standard Error

2.1477

Observations

ANOVA df

F Significance F

Regression

1009.84

336.61

Residual

258.31

4.61

Total

1268.15

72.97 2.42975E-19

Coefficients

Standard Error

t Stat

Pvalue

Lower 95%

Upper 95%

Intercept

-3.8831

1.5015

-2.5861

0.0123

-6.8909

-0.8752

Single-Fam (%)

0.7977

0.0941

8.4778

0.0000

0.6092

0.9862

Unemp. Rate (%)

0.6245

0.1216

5.1357

0.0000

0.3809

0.8681

Batch. Degree (%)

-0.1696

0.0815

-2.0816

0.0420

-0.3329

-0.0064

SUMMARY OUTPUT (high school data included)

Regression Statistics Multiple R

0.8924

R Square

0.7963

Adjusted R Square

0.7815

Standard Error

2.1671

Observations

ANOVA df

F Significance F

Regression

1009.84

252.46

Residual

55 258.3095132 4.6965366

Total

53.75 2.27236E-18

1268.15

Coefficients

Standard Error

t Stat

Pvalue

Lower 95%

Upper 95%

Intercept

-3.8073

3.0436

-1.2510

0.2162

-9.9068

2.2921

Single-Fam (%)

0.7976

0.0950

8.3924

0.0000

0.6071

0.9880

Unemp. Rate (%)

0.6241

0.1237

5.0461

0.0000

0.3762

0.8719

Batch. Degree (%)

-0.1702

0.0846

-2.0111

0.0492

-0.3398

-0.0006

High Sch. (%)

-0.0034

0.1195

-0.0287

0.9772

-0.2429

0.2360

A) It doesn't matter which she uses, the results are virtually the same in either case. B) Angela should use the data that includes the high school information, because more

information is always better than less information. C) Angela should use the data that includes the high school information, because the calculated F value is lower. D) Angela should include the high school data because the P-value is 0.977, close to 1. E) Angela should exclude the high school data because the adjusted R-squared value is a little higher than in the data that includes the high school information.

1130) When does multicollinearity occur in a multiple regression analysis? A) Dependent variables are highly correlated. B) Independent variables are minimally correlated. C) Independent variables are highly correlated. D) Independent variables have no correlation.

1131) What is it called when the independent variables are highly correlated? A) Autocorrelation B) Multicollinearity C) Homoscedasticity D) Zero correlation

1132) If the correlation between the two independent variables of a regression analysis is 0.11

and each independent variable is highly correlated to the dependent variable, what does this indicate? A) Multicollinearity between these two independent variables. B) Negative relationship is not possible. C) Only one of the two independent variables will explain a high percent of the variation. D) An effective regression equation.

1133) What does the correlation matrix for a multiple regression analysis contain? A) Multiple correlation coefficients B) Simple correlation coefficients C) Multiple coefficients of determination D) Multiple standard errors of estimate

1134) The following summary is from home heating costs, using mean outside temperature as

X1, the number of centimeters of insulation as X2 and the presence of a garage as X3. Regression output

Confidence interval

Variables

Coefficients

Std. error

t( df=16)

p-value

95% lower

95%upper

Intercept

172.3701

27.8057

6.199

1.27E-05

113.4245

231.3156

tempC

-10.5475

2.6391

-3.997

.0010

-16.1422

-4.9528

Insulation(cm)

-2.9938

1.5386

-1.946

.0695

-6.2556

0.2679

garage

72.7360

21.8811

3.324

.0043

26.3501

119.1219

Mean outside

1134.1) Is the presence of the independent variable garage significant in predicting heating costs,

when tested at the 0.05 level of significance? A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the garage should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the garage should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the garage should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the garage should be included in the analysis.

1134.2) Is the presence of the independent variable garage significant in predicting heating costs,

when tested at the 0.01 level of significance? A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the garage should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the garage should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the garage should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the garage should be included in the analysis.

1135) It is thought that there are a variety of factors that affect a teacher's salary. Salary ($000)y Years of Experience x1

Principal’s Ratingx2

PhD*x3

55.1

57.6

53.3

62.6

60.8

72.6

55.7

49.7

54.6

75.8

70.7

62.4

57.6

65.8

54.7

56.8

66.8

*1=yes, 0=no Regression output

Confidence interval

Variables

Coefficients

Std. error

t( df=16)

p-value

95% lower

Intercept

41.8128

4.5217

9.247

8.07E08

32.2273 51.3983

0.8981

0.2069

4.341

.0005

0.4595

1.3367

0.2307

0.0742

3.109

.0068

0.0734

0.3879

-4.0145

2.8644

-1.401

.1802

-10.0868

2.0578

95% upper

1135.1) Using the printout and sample data, determine whether the holding of a PhD degree is a

significant variable when tested at the 5% level of significance. A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the holding of a PhD should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the PhD should be included in the analysis.

1135.2) Using the following printout and sample data, determine whether the holding of a PhD

degree is a significant variable when tested at the 10% level of significance. A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the holding of a PhD should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the PhD should be included in the analysis.

1136) It is thought that there are a variety of factors that affect a teacher's salary.

x1 is years of teaching experience, x2 is principal's rating and x3 is the presence of a PhD or not. Regression output Confidence interval Variables

Coefficients

Std. error

t( df=16)

p-value

95% lower

95% upper

Intercept

47.9231

5.8593

8.179

4.16E-07

35.5019

60.3443

0.3156

0.2681

1.177

.2564

-0.2528

0.8839

0.2058

0.0961

2.140

.0481

0.0020

0.4096

9.3880

3.7118

2.529

.0223

1.5193

17.2567

1136.1) Using the following printout and sample data, determine whether the holding of a PhD

1136.2) Using the following printout and sample data, determine whether the holding of a PhD

degree is a significant variable when tested at the 1% level of significance. A) Since the p-value is less than the level of significance, the null hypothesis is rejected, and so the holding of a PhD should be included in the analysis. B) Since the p-value is less than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. C) Since the p-value is more than the level of significance, the null hypothesis is accepted, and so the PhD should not be included in the analysis. D) Since the p-value is more than the level of significance, the null hypothesis is rejected, and so the PhD should be included in the analysis.

1137) It has been hypothesized that overall academic success for freshmen at college as

measured by grade point average (GPA) is a function of IQ scores (X1), hours spent studying each week (X2) and one's high school average (X3). Suppose the regression equation is: Y' = -6.9 + 0.055X1 + 0.107X2 + 0.0083X3. The multiple standard error is 6.313 and R2 = 0.826.

1137.1) What is the predicted GPA for a student with an IQ of 108, 32 hours spent studying per

week and a high school average of 82? A) 3.1446 B) 2.9306 C) 0.428 D) 10.0446 E) 13.1892

1137.2) What will the GPA be if the number of hours spent studying is 30 the IQ is 108, and the

high school average is 82? A) 3.1446 B) 2.9306 C) 0.428 D) 10.0446 E) 13.1892

1137.3) Assuming other independent variables are held constant, what effect on the GPA will

there be if the numbers of hours spent studying per week increases from 32 to 36? A) 3.1446 B) -0.824 C) +0.428 D) -0.428 E) +0.824

1137.4) For which independent variable does a unit change have the least effect on GPA? A) IQ scores (X1) B) hours spent studying each week (X2) C) high school average (X3)

1137.5) For which independent variable does a unit change have the greatest effect on the GPA? A) IQ scores (X1) B) hours spent studying each week (X2) C) high school average (X3)

1137.6) How many dependent variables are in the regression equation? A) One B) Two C) Three D) Four

1137.7) How will a student's GPA be affected if an additional hour is spent studying each

weeknight? A) Increases by 0.535 B) Decreases by 0.535 C) Increases by 0.107 D) Decreases by 0.107 E) Increases by 0.0083

1138) Twenty-one executives in a large corporation were randomly selected for a study in

which several factors were examined to determine their effect on annual salary (expressed in $000's). The factors selected were age, seniority, years of college, number of company divisions they had been exposed to and the level of their responsibility. A regression analysis was performed using a popular spreadsheet program with the following regression output: Constant

23.00371

Std Error of y estimate

2.91933

0.91404

No. of Observations

Degrees of Freedom

15 Age

Sen

Educ

# of Div

Level

X Coefficients

-0.031

0.381

1.452

-0.089

3.554

Std Err of Coef

0.183

0.158

0.387

0.541

0.833

1138.1) Determine the multiple regression equation. A) Y' = 23.004 - 0.031X1 + 0.381X2 + 1.452X3 - 0.089X4 + 3.554X5 B) Y' = -23.004 - 0.031X1 + 0.381X2 + 1.45X3 - 0.089X4 + 3.554X5 C) Y' = 23.004 - 0.031X1 + 0.381X2 + 1.452X3 + 0.089X4 - 3.554X5 D) Y' = 23.004 - 0.031X1 - 0.381X2 - 1.452X3 - 0.089X4 + 3.554X5 E) Y' = -23.004 + 0.031X1 - 0.381X2 - 1.45X3 + 0.089X4 - 3.554X5

1138.2) Which of the following has the most influence on salary--20yearsofseniority, 5 years of

college or attaining 55 years of age? A) 20 years of seniority B) 5 years of college C) attaining 55 years of age D) seniority, education and age all have equal influence on salary

1138.3) What is the effect on salary for an increase of one level of responsibility if the other

variables are held constant? A) +$3,554 B) -$3,554 C) +$833 D) +$8330

1138.4) What is the effect on salary of an increase in age of two years if other variables are held

constant? A) -$62 B) -$31 C) +$31 D) +$62

1138.5) What is the proportion of the variation in salary accounted for by the set of independent

variables? A) 91.4% B) 29.19% C) 83.3% D) 54.1% E) 9.56%

1138.6) What is the value of the denominator in the calculation of the multiple standard error of

estimate? A) 15 B) 21 C) 6 D) 5

1139) A real estate agent developed a model to relate a house's selling price (Y) to the area of

floor space (X) and the area of floor space squared (X2). The multiple regression equation for this model is: Y = 125 - 3X + X2 where: Y = selling price (times $1,000) X = square feet of floor space (times 100)

1139.1) What is the y- intercept (a)? A) $125 000 B) $125 C) $3000 D) $-3000

1139.2) What is the selling price of a house with 1,000 square feet? A) $305 000 B) $125 000 C) $300 000 D) $195 000

1139.3) What is the selling price of a house with 1,500 square feet? A) $305 000 B) $125 000 C) $300 000 D) $1500 000

1139.4) What is the selling price of a house with 2,000 square feet? A) $305 000 B) $125 000 C) $300 000 D) $465 000

1139.5) What is the difference in selling prices of a house with 1,600 square feet and one with

1,700 square feet? A) $30 000 B) $3000 C) $363 000 D) $333 000

1139.6) What is the difference in selling prices of a house with 1,700 square feet and one with

1,800 square feet? A) $30 000 B) $3000 C) $363 000 D) $32 000

1139.7) What is the difference in selling prices of a house with 1,650 square feet and one with

1,750 square feet? A) $30 000 B) $3000 C) $31 000 D) $32 000

1140) Twenty-one executives in a large corporation were randomly selected to study the effect

of several factors on annual salary (expressed in $000s). The factors selected were age, seniority, years of college, number of company divisions they had been exposed to and the level of their responsibility. The results of the regression analysis follow: Constant

23.00371

Std Error of y estimate

2.91933

0.91404

Degrees of Freedom

15 Age

Seniority

Years of College

#Divisions

Level

Regression Coefficients

-0.031

0.381

1.452

-0.089

3.554

Coefficients Std Error

0.183

0.158

0.387

0.541

0.833

1140.1) Test the hypothesis that the regression coefficient for age is equal to 0 at the 0.05

significance level. Report the critical value, the calculated test-statistic, and your decision. A) t-critical = ±2.131, t-calculated = -0.169, fail to reject. B) t-critical = ±2.131, t-calculated = -0.183, fail to reject. C) t-critical = ±1.753, t-calculated = -0.169, fail to reject. D) t-critical = ±1.753, t-calculated = -0.169, reject.

1140.2) Test the hypothesis that the regression coefficient for education is equal to 0 at the 0.05

significance level. Report the critical value, the calculated test-statistic, and your decision. A) t-critical = ±2.131, t-calculated = 3.752, reject the null hypothesis and conclude that education and salary are significantly related. B) t-critical = ±2.131, t-calculated = 3.752, fail to reject. C) t-critical = ±1.753, t-calculated = -0.169, fail to reject. D) t-critical = ±1.753, t-calculated = -3.752, reject the null hypothesis and conclude that education and salary are significantly related.

1141) A multiple regression analysis showed the following ANOVA table result. ANOVA df

p-value

0.425

0.659

Regression

14.001

7.000

Residual

395.629

16.485

Total

409.630

Based on the information in the ANOVA, what is the decision regarding the global null hypothesis? A) The p-value 0.659 is quite large, so we fail to reject the null hypothesis and conclude that there is no relationship between the dependent variable and the independent variables. B) The p-value 0.659 is quite large, so we reject the null hypothesis and conclude that there is a relationship between the dependent variable and the independent variables. C) The p-value, 0.659 is larger than the F value, so we reject the null hypothesis and conclude that there is no relationship between the dependent variable and the independent variables.

1142) In a multiple regression analysis, the following correlation matrix was computed. Y

0.404

0.993

0.362

0.345

-0.718

0.375

0.973

0.357

0.980

0.366

1142.1) Which independent variable(s) are highly correlated with the dependent variable? A) X1 B) X2 C) X3 D) X1 and X4 E) X2 and X4

1142.2) What does the correlation matrix suggest about the independent variables? A) X1 and X2 are correlated. B) No correlation between the independent variables. C) All 4 independent variables are highly correlated with each other, therefore

multicollinearity exists. D) X1 and X4. E) X2 and X4 are correlated as well as X1 and X3; therefore multicollinearity exists.

1143) A multiple regression analysis showed the following ANOVA table result ANOVA df

p-value

5.118166

0.001742

Regression

151326.7

37831.67

Residual

332624.1

7391.646

Total

483950.8

1143.1) Based on the information in the ANOVA, how many independent variables were

included in the multiple regression analysis? A) 1 B) 2 C) 3 D) 4 E) 5

1143.2) Based on the information in the ANOVA, what is the decision regarding the global null

hypothesis? A) The p-value 0.001742 is quite small, so we reject the null hypothesis and conclude that there is a relationship between the dependent variable and at least one of the independent variables. B) The p-value 0.001742 is quite large, so we fail to reject the null hypothesis and conclude that there is a relationship between the dependent variable and the independent variables. C) The p-value, 0.001742 is larger than the F value, so we reject the null hypothesis and conclude that there is no relationship between the dependent variable and the independent variables.

1144) A multiple regression analysis showed the following results of the individual independent

variables. Coefficients

Standard Error

t-Stat

p-value

Intercept

139.577

84.235

1.657

0.104

-0.135

5.698

-0.024

0.981

3.734

1.220

3.062

0.004

2.448

26.524

-0.376

0.709

-9.976

1.044

2.345

0.024

1144.1) Which independent variables are significantly related to the dependent variable? A) X2 and X4 are significantly related to the dependent variable indicated by their very

small p-values. B) No significant relationship between the independent variables and the dependent variable. C) All 4 independent variables are highly correlated with each other, therefore they are all significantly related to the dependent variable. D) X1 and X3 are significantly related to the dependent variable indicated by their large p-values.

1144.2) In stepwise regression, which independent variable would most likely be added first? A) X1 B) X2 C) X3 D) X4

1145) A random selection of cities were studied throughout Canada to determine the number of

deaths Y, based on the variables: Cases X1, Hospitalizations X2 and Population (in millions) X3 Source

Regression

119.06

Residual

Total

120.88 Coefficients

Std Err

Intercept

-0.78

0.42

0.01

0.003

0.13

0.03

-1.13

0.73

Y X1

0.95

0.98

0.91

0.87

0.94

1145.1) How many independent variables are in the regression model? A) 0 B) 1 C) 2 D) 3 E) 4

0.87

1145.2) How many dependent variables are in the regression model? A) 0 B) 1 C) 2 D) 4

1145.3) Which independent variable has the strongest relationship with the dependent variable? A) Deaths B) Cases C) Hospitalizations D) Population

1145.4) Which independent variable has neither the strongest nor weakest relationship with the

dependent variable? That is the second strongest relationship. A) Deaths B) Cases C) Hospitalizations D) Population

1145.5) Which independent variable has the weakest relationship with the dependent variable? A) Deaths B) Cases C) Hospitalizations D) Population

1145.6) What percent of the change in deaths in a city is explained by the change in the

combination of Cases, Hospitalizations and Population of the city? A) 0.455 B) 0.675 C) 0.985 D) 0.992

1145.7) Compute r2 A) 0.992 B) 0.675 C) 0.985 D) 0.455

1145.8) Calculate the coefficient of multiple determination. A) 0.455 B) 0.985 C) 0.675 D) 0.992

1145.9) When making forecast for the number of deaths, what is the standard error of estimate? A) 0.992 B) 0.985 C) 0.675 D) 0.455

1145.10)

Predict the number of deaths in a city which has 1000 cases, 100 hospitalizations and a population of 2.5 (million). A) 0 B) 1.4 C) 5.7 D) 19.4

1145.11)

Predict the number of deaths in a city which has 500 cases, 20 hospitalizations and a population of 1 (million). A) 0 B) 1.4 C) 5.7 D) 19.4

1145.12)

Predict the number of deaths in a city which has 100 cases, 10 hospitalizations and a population of 0.1 (million). A) 0 B) 1.4 C) 5.7 D) 19.4

1145.13) What is the null hypothesis at the 0.05 significance level for the global test? A) H0: X1=X2=X3=0 B) H0: X1≠X2≠X3≠0 C) H0: Ɓ1=Ɓ2=Ɓ3=0 D) H0: Ɓ1≠Ɓ2≠Ɓ3≠0

1145.14) What is the alternative hypothesis at the 0.05 significance level for the global test? A) H1: Ɓ1≠ Ɓ2≠ Ɓ3≠0 B) H1:At least one Ɓ≠0 C) H1: X1≠X2≠X3≠0 D) H1: All the B's =0

1145.15) A) B) C) D)

What is the critical F value at the 0.05 significance level? 6.59 7.85 8.45 9.12

1145.16) A) B) C) D)

What is the critical F value at the 0.01 significance level? 6.59 28.7 7.59 16.7

1145.17) A) B) C) D)

What is the computed F Value? 6.59 1.82 87.2 16.7

1145.18)

Based on the computed F-Value and the Critical F value at a significance level of 0.05 what conclusions can you reach about the independent variables? A) Reject the null hypothesis and conclude that none on the independent variables are useful at predicting Y. B) Reject the null hypothesis and conclude at least one of the independent variables are useful at predicting Y. C) Do not reject the H0 and conclude at least one of the variables is useful to predict Y. D) Reject H0 and conclude all of the independent variables are useful to predict Y.

1145.19)

Based on the computed F-Value and the Critical F value at a significance level of 0.01 what conclusions can you reach about the independent variables? A) Reject the null hypothesis and conclude that none on the independent variables are useful at predicting Y. B) Reject the null hypothesis and conclude at least one of the independent variables are useful at predicting Y. C) Do not reject the H0 and conclude at least one of the variables is useful to predict Y. D) Reject H0 and conclude all of the independent variables are useful to predict Y.

1145.20)

Perform the test of hypothesis to determine if any of the independent variables are related to the dependent variable. Specifically, what is the null hypothesis? A) Ɓ1=Ɓ2=Ɓ3=0 B) Ɓ1=0,Ɓ2=0 Ɓ3=0 C) Ɓ1≠0,Ɓ2≠0,Ɓ3≠0 D) At least one Ɓ ≠0

1145.21)

Perform the test of hypothesis to determine if any of the independent variables are related to the dependent variable. Specifically, what is the alternative hypothesis? A) Ɓ1=Ɓ2=Ɓ3=0 B) Ɓ1=0,Ɓ2=0 Ɓ3=0 C) Ɓ1≠0,Ɓ2≠0,Ɓ3≠0 D) At least one Ɓ ≠0

1145.22)

Perform the test of hypothesis to determine if any of the independent variables are related to the dependent variable. Specifically, what is/are the critical value(s) at a significance level of 0.05? A) +2.132 B) -2.132 C) ±2.365 D) ±2.776

1145.23)

Perform the test of hypothesis to determine if any of the independent variables are related to the dependent variable. Specifically which variable(s) would you remove after comparing the Test Statistic with the Critical value at the 0.05 significance level? A) Keep all 3 variables B) Remove all 3 variables C) Keep Cases and Hospitalizations and remove Population D) Keep Cases and Population and remove Hospitalization. E) Keep only Hospitalizations and remove both Cases and Population

1145.24)

Perform the test of hypothesis to determine if any of the independent variables are related to the dependent variable. Specifically which variable(s) would you remove after comparing the Test Statistic with the Critical value at the 0.01 significance level? A) Keep all 3 variables. B) Remove all 3 variables. C) Keep Cases and Hospitalizations and remove Population. D) Keep Cases and Population and remove Hospitalization. E) Keep only Hospitalizations and remove both Cases and Population.

Answer Key Test name: chapter 13 489) B 490) Section Break 490.1) D 490.2) C 490.3) B 490.4) C 490.5) A 491) Section Break 491.1) B 491.2) E 491.3) A 491.4) E 491.5) A 491.6) B 491.7) C 492) Section Break 492.1) D 492.2) E 492.3) A 492.4) A 493) Section Break 493.1) A 493.2) C 493.3) D 493.4) D 494) C 495) D 496) B 497) C 498) A 499) D 500) A 501) B 502) B 503) Section Break 503.1) D 503.2) A

503.3) B 504) E 505) B 506) B 507) B 508) Section Break 508.1) A 508.2) B 508.3) E 508.4) C 508.5) A 508.6) A 508.7) B 508.8) D 508.9) C 508.10) E 508.11) B 508.12) C 509) A 510) C 511) D 512) B 513) B 514) C 515) A 516) B 517) E 518) B 519) C 520) D 521) C 522) B 523) C 524) A 525) A 526) C 527) A 528) E 529) C 530) C

531) B 532) A 533) C 534) C 535) E 536) C 537) B 538) B 539) A 540) C 541) E 542) C 543) B 544) D 545) B 546) Section Break 546.1) A 546.2) A 547) Section Break 547.1) C 547.2) C 548) Section Break 548.1) A 548.2) C 549) Section Break 549.1) A 549.2) B 549.3) C 549.4) C 549.5) B 549.6) A 549.7) C 550) Section Break 550.1) A 550.2) A 550.3) A 550.4) A 550.5) A 550.6) A 551) Section Break

551.1) A 551.2) D 551.3) A 551.4) D 551.5) A 551.6) D 551.7) C 552) Section Break 552.1) A 552.2) A 553) A 554) Section Break 554.1) E 554.2) E 555) Section Break 555.1) D 555.2) A 556) Section Break 556.1) A 556.2) B 557) Section Break 557.1) D 557.2) B 557.3) C 557.4) B 557.5) D 557.6) C 557.7) C 557.8) B 557.9) C 557.10) D 557.11) C 557.12) B 557.13) C 557.14) B 557.15) A 557.16) D 557.17) C 557.18) B 557.19) B

557.20) B 557.21) D 557.22) D 557.23) C 557.24) B

Student name:__________ 1146) i. The chi-square goodness-of-fit test is appropriate for nominal and ordinal levels of

data. ii. Chi-square test statistic used in a goodness-of-fit test has k - 1 degrees of freedom. iii. The chi-square goodness-of-fit test can be applied if there are equal or unequal expected frequencies. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1147) i. Chi-square test statistic used in a goodness-of-fit test has k - 1 degrees of freedom.

ii. The chi-square goodness-of-fit test can be applied if there are equal or unequal expected frequencies. iii. For a goodness-of-fit test, the number of degrees of freedom is determined by k - 2, where k is the number of categories. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1148) i. The chi-square goodness-of-fit test can be applied if there are equal or unequal

expected frequencies. ii. For a goodness-of-fit test, the number of degrees of freedom is determined by k - 2, where k is the number of categories. iii. The sum of the expected frequencies in a goodness-of-fit test need not equal the sum of the observed frequencies. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i) is a correct statement, but (ii) and (iii) are false.

1149) i. For a goodness-of-fit test, the number of degrees of freedom is determined by k - 2,

where k is the number of categories. ii. The sum of the expected frequencies in a goodness-of-fit test need not equal the sum of the observed frequencies. iii. A goodness-of-fit test is a nonparametric test involving a set of observed frequencies and a corresponding set of expected frequencies. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (iii) is a correct statement, but (i) and (ii) are false.

1150) i. The sum of the expected frequencies in a goodness-of-fit test need not equal the sum of

the observed frequencies. ii. A goodness-of-fit test is a nonparametric test involving a set of observed frequencies and a corresponding set of expected frequencies. iii. For a goodness-of-fit test, the following are possible null and alternate hypotheses; Null: Sales are uniformly distributed among the five locations. Alternate: Sales are not uniformly distributed among the five locations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1151) i. A goodness-of-fit test is a nonparametric test involving a set of observed frequencies

and a corresponding set of expected frequencies. ii. For a goodness-of-fit test, the following are possible null and alternate hypotheses: Null: Sales are uniformly distributed among the five locations. Alternate: Sales are not uniformly distributed among the five locations. iii. In the goodness-of-fit test, the chi-square distribution is used to determine how well an observed set of observations "fits" an "expected" set of observations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1152) i. For a goodness-of-fit test, the following are possible null and alternate hypotheses.

Null: Sales are uniformly distributed among the five locations. Alternate: Sales are not uniformly distributed among the five locations. ii. In the goodness-of-fit test, the chi-square distribution is used to determine how well an observed set of observations "fits" an "expected" set of observations. iii. The sum of the expected frequencies and the sum of the observed frequencies must be equal. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1153) i. In the goodness-of-fit test, the chi-square distribution is used to determine how well an

observed set of observations "fits" an "expected" set of observations. ii. The sum of the expected frequencies and the sum of the observed frequencies must be equal. iii. If the computed value of chi-square is less than the critical value, reject the null hypothesis at a predetermined level of significance. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1154) i. The sum of the expected frequencies and the sum of the observed frequencies must be

equal. ii. If the computed value of chi-square is less than the critical value, reject the null hypothesis at a predetermined level of significance. iii. If there are only two cells in a goodness-of-fit test, we should expect 5 or more frequencies. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1155) i. If the computed value of chi-square is less than the critical value, reject the null

hypothesis at a predetermined level of significance. ii. If there are only two cells in a goodness-of-fit test, we should expect 5 or more frequencies. iii. Chi-square goodness-of-fit test is the appropriate statistical test to use when you wish to determine how well an observed set of data fits an expected set of data. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1156) i. If there are only two cells in a goodness-of-fit test, we should expect 5 or more

frequencies. ii. Chi-square goodness-of-fit test is the appropriate statistical test to use when you wish to determine how well an observed set of data fits an expected set of data. iii. The null hypothesis in the goodness-of-fit test is that there is no difference. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1157) i. Chi-square goodness-of-fit test is the appropriate statistical test to use when you wish to

determine how well an observed set of data fits an expected set of data. ii. The null hypothesis in the goodness-of-fit test is that there is no difference. iii. The alternative hypothesis states that there is a difference between the observed frequencies and the expected frequencies in a goodness-of-fit test. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1158) i. The null hypothesis in the goodness-of-fit test is that there is no difference.

ii. The alternative hypothesis states that there is a difference between the observed frequencies and the expected frequencies in a goodness-of-fit test. iii. The number of degrees of freedom appropriate for the chi-square goodness-of-fit test is the number of categories minus 1. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1159) i. The alternative hypothesis states that there is a difference between the observed

frequencies and the expected frequencies in a goodness-of-fit test. ii. The number of degrees of freedom appropriate for the chi-square goodness-of-fit test is the number of categories minus 1. iii. If there are extremely large differences between observed and expected frequencies the correct decision is to reject H0. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1160) i. The number of degrees of freedom appropriate for the chi-square goodness-of-fit test is

the number of categories minus 2. ii. If there are extremely large differences between observed and expected frequencies the correct decision is to reject H0. iii. There are 2 degrees of freedom for a contingency table classifying three levels of income with each gender. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1161) i. For a goodness-of-fit test, the following are possible null and alternate hypotheses.

Null: Sales are uniformly distributed among the five locations. Alternate: Sales are not uniformly distributed among the five locations. ii. The number of degrees of freedom appropriate for the chi-square goodness-of-fit test is the number of categories minus 1. iii. If there are extremely large differences between observed and expected frequencies the correct decision is to accept H0. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1162) i. For a goodness-of-fit test, the number of degrees of freedom is determined by k - 2,

where k is the number of categories. ii. The sum of the expected frequencies in a goodness-of-fit test need not equal the sum of the observed frequencies. iii. If the computed value of chi-square is less than the critical value, reject the null hypothesis at a predetermined level of significance. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1163) i. The chi-square goodness-of-fit test can be applied if there are equal or unequal

expected frequencies. ii. For a goodness-of-fit test, the following are possible null and alternate hypotheses. Null: Sales are uniformly distributed among the five locations. Alternate: Sales are not uniformly distributed among the five locations. iii. The number of degrees of freedom appropriate for the chi-square goodness-of-fit test is the number of categories minus 1. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1164) i. chi-square test statistic used in a goodness-of-fit test has k - 2 degrees of freedom.

ii. A goodness-of-fit test is a nonparametric test involving a set of observed frequencies and a corresponding set of expected frequencies. iii. For a goodness-of-fit test, the following are possible null and alternate hypotheses. Null: Sales are uniformly distributed among the five locations. Alternate: Sales are not uniformly distributed among the five locations. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1165) i. If the computed value of chi-square is less than the critical value, reject the null

hypothesis at a predetermined level of significance. ii. The alternative hypothesis states that there is a difference between the observed frequencies and the expected frequencies in a goodness-of-fit test. iii. There are 2 degrees of freedom for a contingency table classifying three levels of income with each gender. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1166) A question has these possible choices—excellent, very good, good, fair and

unsatisfactory. How many degrees of freedom are there, using the goodness-of-fit test to the sample results? A) 0 B) 2 C) 4 D) 5

1167) What is the critical value at the 0.05 level of significance for a goodness-of-fit test if

there are six categories? A) 3.841 B) 5.991 C) 7.815 D) 11.070

1168) What is our decision regarding the differences between the observed and expected

frequencies if the critical value of chi-square is 9.488 and the computed value is 6.079? A) Due to chance; do not reject the null hypothesis. B) Not due to chance; reject the null hypothesis. C) Not due to chance; do not reject the alternate hypothesis. D) Too close; reserve judgment.

1169) Canadian Accounting classifies accounts receivable as "current", "late", and "not

collectible". Industry figures show that 60% of A/R are current, 30% are late, and 10% are uncollectible. A law firm in Markham Ontario has 500 accounts receivable: 320 are current, 120 are late and 60 are not collectible. Are these numbers in agreement with the industry distribution? Goodness of Fit Test observed

expected

O-E

(O-E)2/E

% of chisq

320

300.000

20.000

1.333

14.29

120

150.000

-30.000

6.000

64.29

50.000

10.000

2.000

21.43

500

500.000

0.000

9.333

100.00

9.33

chi-square

.0094

p-value

Using the data from this MegaStat printout, you determine: A) the Markham firm's data reflect the national average, when tested at the 0.10 level of significance. B) the Markham firm's data reflect the national average, when tested at the 0.05 level of significance. C) the Markham firm's data reflect the national average, when tested at the 0.01 level of significance. D) the Markham firm's data do not reflect the national average, when tested above a 0.01 level of significance.

1170) Canadian Accounting classifies accounts receivable as "current", "late" and "not

collectible". Industry figures show that 60% of A/R are current, 30% are late and 10% are uncollectible. A law firm in Markham Ontario has 500 accounts receivable: 310 are current, 125 are late and 65 are not collectible. Are these numbers in agreement with the industry distribution? Goodness of Fit Test Observed

Expected

O-E

(O-E)2/E

% of chisq

310

300.000

10.000

0.333

3.70

125

150.000

-25.000

4.167

46.30

50.000

15.000

4.500

50.00

500

500.000

0.000

9.000

100.00

9.00

chi-square

.0111

p-value

1171) For any chi-square goodness-of-fit problem, the number of degrees of freedom is found

by: A) B) C) D)

n - k - 1. k - 1. n + 1. n + k.

1172) When determining how well an observed set of frequencies fit an expected set of

frequencies the test is the: A) F test. B) t test. C) goodness-of-fit test. D) test for association.

1173) In the chi-square test, the null hypothesis (no difference between sets of observed and

expected frequencies) is rejected when the: A) computed chi-square is less than the critical value. B) difference between the observed and expected frequencies is significant. C) difference between the observed and expected frequencies is small. D) difference between the observed and expected frequencies occurs by chance.

1174) The computed chi-square value is positive because the difference between the observed

and expected frequencies is: A) squared. B) linear. C) uniform. D) always positive.

1175) A student asked a statistics professor if grades were marked "on the curve." The professor

decided to give the student a project to determine if last year's statistics grades were normally distributed. The professor told the student that last year's mean mark was 70 with a standard deviation of 10 and to use the following results. Letter Grade

Grade Average

Observed

90 and above

80 up to 90

70 up to 80

60 up to 70

50 up to 60

Under 50

1175.1) What is the alternative hypothesis? A) The letter grades are evenly distributed. B) The letter grades are not evenly distributed. C) The letter grades are normally distributed. D) The letter grades are not normally distributed. E) The letter grades are unfairly distributed.

1175.2) What is the expected number of grades above B? A) 18.25 B) 20.00 C) 13.59 D) 15.87 E) 15.63

Expected

1175.3) What is the expected number of C's? A) 39.25 B) 34.13 C) 13.59 D) 30.00 E) 15.87

1175.4) What is the expected number of F's? A) 10.00 B) 2.28 C) 2.62 D) 13.59 E) 4.56

1175.5) What is the critical value of chi-square at the 0.05 level? A) 12.833 B) 11.070 C) 12.592 D) 14.449 E) 19.675

1175.6) What is the calculated value of chi-square? A) 29.76 B) 14.20 C) 14.88 D) 28.36 E) 12.59

1175.7) What is your decision if α = 0.05? A) The letter grades are evenly distributed. B) The letter grades are not evenly distributed. C) The letter grades are normally distributed. D) The letter grades are not normally distributed. E) The letter grades are unfairly distributed.

1175.8) What is your decision if α = 0.05? Goodness of Fit Test

A) B) C) D) E)

Observed

Expected

O-E

(O-E)2/E

% of chisq

2.622

2.378

2.157

7.60

15.629

4.372

1.223

4.31

39.250

0.751

0.014

0.05

39.250

-9.250

2.180

7.69

15.629

-5.629

2.027

7.15

2.622

7.378

20.761

73.20

115

115.000

0.000

28.361

100.00

28.36

chi-square

3.09E-05

p-value

The letter grades are evenly distributed. The letter grades are not evenly distributed. The letter grades are normally distributed. The letter grades are not normally distributed. The letter grades are unfairly distributed.

1175.9) Using the data from this MegaStat printout, you determine: Goodness of Fit Test Observed

Expected

O-E

(O-E)2/E

% of chisq

2.622

2.378

2.157

7.60

15.629

4.372

1.223

4.31

39.250

0.751

0.014

0.05

39.250

-9.250

2.180

7.69

15.629

-5.629

2.027

7.15

2.622

7.378

20.761

73.20

115

115.000

0.000

28.361

100.00

28.36

chi-square

3.09E-05

p-value

A) the letter grades are evenly distributed when tested at the 0.05 level of significance. B) the letter grades are not normally distributed when tested at the 0.01 level of

significance. C) the letter grades are normally distributed when tested at the 0.05 level of significance. D) the letter grades are not normally distributed when tested at the 0.05 level of significance. E) the letter grades are not normally distributed when tested at either the 0.01 or 0.05 level of significance.

1176) Three new colors have been proposed for the Jeep Grand Cherokee vehicle. They are

silvered-blue, almond, and willow green. The null hypothesis for a goodness-of-fit test would be A) willow green preferred over the other colours. B) no preference between the colours. C) any one color preferred over the other colours. D) impossible to determine.

1177) A distributor of personal computers has five locations in the city. The sales in units for

the first quarter of the year were as follows: Location

Observed Sales (Units)

North Side

Pleasant Township

Southwyck

I-90

Venice Avenue

Total

300

What is the critical value at the 0.01 level of risk? A) 7.779 B) 15.033 C) 13.277 D) 5.412

1178) What is our decision for a goodness-of-fit test with a computed value of chi-square of

1.273 and a critical value of 13.388? A) Do not reject the null hypothesis. B) Reject the null hypothesis. C) Unable to reject or not reject the null hypothesis based on data. D) Should take a larger sample.

1179) Which of the following are correct statements regarding the goodness-of-fit test? A) Data may be of nominal scale. B) Population must be normal. C) All the expected frequencies must be equal. D) All of the choices are correct.

1180) In a contingency table suppose that we are comparing males versus females against five

glades: A, B, C, D and F. The degrees of freedom will be: A) 10 B) 8 C) 4 D) 6

1181) Suppose that we wish to test the null hypothesis that for 3 cells, A, B, and C, the cell

categories are equal. We observed 8 data in cell A, 13 in cell B, and 9 in cell C. What is the decision rule using the 0.05 significance level? A) 7.815 B) 5.991 C) 43.773 D) 42.557

1182) Suppose that we wish to test the null hypothesis that for 3 cells, A, B, and C, the cell

categories are equal. We observed 8 data in cell A, 13 in cell B, and 9 in cell C. What is the decision regarding the null hypothesis? A) Do not reject the null hypothesis. B) Reject the null hypothesis. C) There is not enough information to reach a decision.

1183) To find the expected frequency in a contingency table: A) take the square root of the degrees of freedom. B) multiply the row and column totals and divide by the grand total. C) use the total number of observations minus one.

1184) i. Nonparametric tests require no assumptions about the shape of the population

distribution. ii. Tests of hypotheses for nominal or ordinal levels of measurement are called nonparametric or distribution-free tests. iii. There is not one, but a family of chi-square distributions. There is a chi-square distribution for 1 degree of freedom, another for 2 degrees of freedom, another for 3 degrees of freedom, and so on. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1185) i. Tests of hypotheses for nominal or ordinal levels of measurement are called

nonparametric or distribution-free tests. ii. There is not one, but a family of chi-square distributions. There is a chi-square distribution for 1 degree of freedom, another for 2 degrees of freedom, another for 3 degrees of freedom, and so on. iii. The shape of the chi-square distribution depends on the size of the sample. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1186) i. There is not one, but a family of chi-square distributions. There is a chi-square

distribution for 1 degree of freedom, another for 2 degrees of freedom, another for 3 degrees of freedom, and so on. ii. The shape of the chi-square distribution depends on the size of the sample. iii. Small differences between observed and expected frequencies are due to chance. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1187) i. The shape of the chi-square distribution depends on the size of the sample.

ii. Small differences between observed and expected frequencies are due to chance. iii. The chi-square distribution with large degrees of freedom approaches a normal distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1188) i. Small differences between observed and expected frequencies are due to chance.

ii. The chi-square distribution with large degrees of freedom approaches a normal distribution. iii. The chi-square distribution is positively skewed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1189) i. The chi-square distribution with large degrees of freedom approaches a normal

distribution. ii. The chi-square distribution is positively skewed. iii. Nonparametric tests of hypotheses, which are also called distribution free tests, require the population to be normally distributed. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1190) i. The chi-square distribution is positively skewed.

ii. Nonparametric tests of hypothesis, which are also called distribution free tests, require the population to be normally distributed. iii. The computed value of chi-square is always positive because the difference between the observed frequencies and the expected frequencies are squared. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1191) i. Nonparametric tests of hypotheses, which are also called distribution free tests, require

the population to be normally distributed. ii. The computed value of chi-square is always positive because the difference between the observed frequencies and the expected frequencies are squared. iii. The shape of the chi-square distribution changes for each number of degrees of freedom. A) (i), (ii), and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1192) i. The computed value of chi-square is always positive because the difference between

the observed frequencies and the expected frequencies are squared. ii. The shape of the chi-square distribution changes for each number of degrees of freedom. iii. The minimum computed value of chi-square is zero. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1193) i. The shape of the chi-square distribution changes for each number of degrees of

freedom. ii. The minimum computed value of chi-square is zero. iii. The chi-square distribution is a positively skewed distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1194) i. The minimum computed value of chi-square is one.

ii. The chi-square distribution is a positively skewed distribution. iii. The lowest level of data for which the chi-square goodness-of-fit test is appropriate is the nominal level. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1195) i. Nonparametric tests of hypotheses, which are also called distribution free tests, require

the population to be normally distributed. ii. The shape of the chi-square distribution changes for each number of degrees of freedom. iii. The chi-square distribution is a positively skewed distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1196) i. Nonparametric tests require no assumptions about the shape of the population

distribution. ii. There is not one, but a family of chi-square distributions. There is a chi-square distribution for 1 degree of freedom, another for 2 degrees of freedom, another for 3 degrees of freedom, and so on. iii. The chi-square distribution with large degrees of freedom approaches a normal distribution. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1197) The chi-square distribution can assume: A) only positive values. B) only negative values. C) negative and positive values or zero. D) only zero.

1198) The chi-square distribution is: A) positively skewed. B) negatively skewed. C) normally distributed. D) negatively or positively skewed.

1199) Two chi-square distributions were plotted on the same chart. One distribution was for 3

degrees of freedom and the other was for 12 degrees of freedom. Which distribution would tend to approach a normal distribution? A) 3 degrees B) 12 degrees C) 15 degrees D) All three distributions would approach a normal distribution

1200) At a recent car show, a sample of 125 people produced the following results. Use the 0.05

significance level to determine if there is a relationship between age and model preferred. Age (in years)

Sports

SUV

Luxury

Total

Under 30

30 to 50

over 50

125

A) Reject the null hypothesis, there is a significant relationship between age and model

preferred at the 5% level of significance. B) Unable to reject the null hypothesis, there is a significant relationship between age and model preferred at the 5% level of significance. C) Reject the null hypothesis, there is insufficient evidence to show a significant relationship between age and model preference. D) Unable to reject the null hypothesis, there is significant relationship between age and model preferred at the 5% level of significance.

1201) The chi-square distribution becomes more symmetrical as: A) number of variables increase. B) the chi-square value increases. C) degrees of freedom decrease. D) degrees of freedom increase.

1202) The chi-square has: A) one distribution. B) two distributions. C) a family of distributions. D) a uniform distribution.

1203) Which of the following are correct statements regarding the chi-square distribution? A) Distribution is negatively skewed B) Chi-square is based on two sets of degrees of freedom, one for the numerator and one

for the denominator. C) Its shape is based on the degrees of freedom.

1204) The personnel manager is concerned about absenteeism. She decides to sample the

records to determine if absenteeism is distributed evenly throughout the six-day workweek. The null hypothesis to be tested is: Absenteeism is distributed evenly throughout the week. The 0.01 level is to be used. The sample results are: Day of Week

Number Absent

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

1204.1) What kind of frequencies are the numbers 12, 9, 11, 10, and 9 called? A) Acceptance B) Critical value C) Expected D) Observed

1204.2) How many degrees of freedom are there? A) 0 B) 3 C) 4 D) 5

1204.3) What is the expected frequency? A) 9 B) 10 C) 11 D) 12

1204.4) What is the calculated value of chi-square? A) 1.0 B) 0.5 C) 0.8 D) 8.0

1204.5) Using the Goodness of Fit Test above, what can you state about the observed absences? Goodness of Fit Test Observed

Expected

O-E

(O-E)2/E

% of chisq

10.000

2.000

0.400

50.00

10.000

-1.000

0.100

12.50

10.000

1.000

0.100

12.50

10.000

0.000

0.00

10.000

-1.000

0.100

12.50

10.000

-1.000

0.100

12.50

60.000

0.000

0.800

100.00

.80

chi-square

.9770

p-value

A) The 0.8 value of chi-square with 5 df, leads us to conclude that there is a significant

difference between the number of absences across the week when tested at the 5% level of significance. B) Absenteeism is distributed evenly throughout the week. The observed differences are due to sampling variation, as supported by the p-value of 0.9770. C) Absenteeism is not distributed evenly throughout the week. The p-value of 0.9770 strongly supports this conclusion. D) The 5df lead us to conclude that absenteeism is distributed evenly throughout the week. E) None of the choices are correct.

1205) Six people have declared their intentions to run for a trustee seat in the next local

election. A political poll is conducted during the campaign among 1,020 voters to determine if there is any clear preference among the voters. The responses are shown below. Candidate:

Responses

180

240

200

130

125

145

1205.1) Determine the null and alternate hypotheses. A) Ho: No preference among candidates exists H1: Preference among candidates. B) Ho: Preference among candidates exists H1: No preference among candidates exists. C) We are unable to determine because there are too many candidates. D) We need more information to determine the null and alternate hypotheses.

1205.2) How many degrees of freedom are there? A) 1 B) 2 C) 3 D) 4 E) 5

1205.3) What is the critical value at the 5% level of significance? A) 11.070 B) 3.841 C) 5.991 D) 9.236 E) 9.438

1205.4) What is the critical value at the 1% level of significance? A) 6.635 B) 9.210 C) 11.345 D) 13.277 E) 15.086

1205.5) What is the expected frequency for each candidate? A) 204 B) 170 C) 510 D) 180

1205.6) If the computed chi-square is 30, what is your decision at the 1% level of significance?

What is your decision at the 5% level of significance? A) Reject H0; preferences among the candidates exist at the 1% level of significance; also reject at the 5% level of significance. B) Reject H0at the 1% level of significance but not at the 5% level of significance. C) Reject H0at the 5% level of significance but not at the 1% level of significance. D) Accept Ho at both the 5% and 1% levels of significance; no preferences among the candidates exist.

1206) In a chi-square goodness-of-fit-test, the larger the difference between the set of expected

frequencies and the set of observed frequencies: A) the more likely we are to conclude that the observed distribution is similar to the expected distribution. B) the more likely it will be that we will not reject the null hypothesis. C) the more likely we will reject the null hypothesis. D) the more likely we will be to not accept the alternative hypothesis.

1207) Which of the following is not a characteristic of the chi square distribution? A) Its shape is based on the sample size. B) It is not negative. C) It is positively skewed. D) It approaches a normal distribution as the degrees of freedom increase.

1208) How many degrees of freedom do we use for the chi square goodness of fit test? A) k, where k represents the number of classes/categories. B) k - 1, where k represents the number of classes/categories. C) k - 1, where k represents the number of data values. D) k, where k represents the number of data values.

1209) A school is trying to determine if there is a relationship between gender and which of its

3 programs that students enroll in. It was observed that 20 females enrolled in accounting, 15 in finance and 25 in marketing. For males, 10 enrolled in accounting, 20 enrolled in finance and 15 enrolled in marketing. What is the chi square value? A) 4.50 B) 5 C) 3.25 D) 4.25

1210) A school is trying to determine if there is a relationship between gender and which of its

3 programs that students enroll. It was observed that 20 females enrolled in accounting, 15 in finance and 25 in marketing. For males, 10 enrolled in accounting, 20 enrolled in finance and 15 enrolled in marketing. Can we conclude that there is a relationship between gender and program? Use the 0.05 significance level. A) There is no evidence of a relationship between gender and program of study. B) There is evidence of a relationship between gender and program of study. C) Not enough information is given to reach a conclusion.

1211) i. For a contingency table, the expected frequency for a cell is found by dividing the row

total by the grand total. ii. The claim that "male and female University of Toledo students prefer different parking lots on campus" is an example of a chi-square null hypothesis. iii. For contingency table analysis using the chi-square test, multiplying the number of rows minus 1 by the number of columns minus 1 will give you the degrees of freedom. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (iii) is a correct statement but not (i) or (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1212) i. The claim that "male and female University of Toledo students prefer different parking

lots on campus" is an example of a chi-square null hypothesis. ii. For a contingency table, the expected frequency for a cell is found by dividing the row total by the grand total. iii. For contingency table analysis using the chi-square test, multiplying the number of rows minus 1 by the number of columns minus 1 will give you the degrees of freedom. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are false statements only (iii) is correct. C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1213) i. The claim that "male and female University of Toledo students prefer different parking

lots on campus" is an example of a chi-square null hypothesis. ii. For contingency table analysis using the chi-square test, multiplying the number of rows minus 1 by the number of columns minus 1 will give you the degrees of freedom. iii. For a contingency table, the expected frequency for a cell is found by dividing the row total by the grand total. A) (i), (ii), and (iii) are all correct statements. B) (ii) is a correct statement but not (i) or (iii). C) (iii) is a correct statement but not (i) or (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1214) Recently, students in a marketing research class were interested in the driving behavior of

students. Specifically, the marketing students were interested if exceeding the speed limit was related to gender. They collected the following responses from 100 randomly selected students: Chi-square Contingency Table Test for Independence Speeds

Does Not Speed

Total

Males

Females

Total

100

9.89

chi-square

.0017

p-value

Using the output from MegaStat for the data given, what can you conclude? A) Gender and speeding are correlated. B) Gender and speeding are not related, based on the low p-value. C) Gender and speeding are related, based on the low p-value. D) The mean of gender equals the mean of speeding. E) No conclusion is possible.

1215) The educational level and the social activity of a sample of executives follow. Chi-square Contingency Table Test for Independence Above Average

Average

Below Average

Total

College

High School

150

Grade School

130

190

Total

110

230

400

83.67

chi-square

2.91E-17

p-value

1215.1) Using the data from this MegaStat printout, you determine: A) social activity and education level are correlated. B) social activity and education level are not related, based on the low p-value. C) social activity and education level are strongly related, based on the low p-value. D) increased levels of education result in increased social activity. E) no conclusion is possible.

1215.2) What does the expected frequency for the "above average" social activity and "high

school" education equal? A) 9.50 B) 60.00 C) 22.50 D) 28.50

1216) The educational level and the social activity of a sample of executives follow. Chi-square Contingency Table Test for Independence Above Average

Average

Below Average

Total

College

High School

Grade School

Total

100

200

6.65

chi-square

.1554

p-value

Using the data from this MegaStat printout, you determine: A) social activity and education level are correlated. B) social activity and education level are not related, when tested at the 0.10 level of significance. C) social activity and education level are strongly related, based on the low p-value. D) increased levels of education result in increased social activity. E) social and education level are not related, when tested at the 0.20 level of significance.

1217) The educational level and the social activity of a sample of executives follow. Chi-square Contingency Table Test for Independence Above Average

Average

Below Average

Total

College

High School

Grade School

Total

205

16.05

chi-square

.0029

p-value

Using the data from this MegaStat printout, you determine: A) social activity and education level are correlated. B) social activity and education level are not related, when tested at the 0.10 level of significance. C) social activity and education level are related, when tested at the 0.01 level of significance. D) increased levels of education result in increased social activity E) social and education level are not related, when tested at the 0.20 level of significance.

1218) The following table shows the adjustment to civilian life and place of residence. Chi-square Contingency Table Test for Independence Residence After Release From Prison

Outstanding adjustment to civilian life

Good Fair adjust Adjustment to to civilian civilian life life

Unsatisfactory Adjustment

Total

Hometown

120

Not Hometown

Total

200

5.73

chi-square

.1256

p-value

1218.1) Using the data from this MegaStat printout, you determine: A) residence after prison release and adjustment to civilian life are not related, when

tested at the 0.10 level of significance. B) residence after prison release and adjustment to civilian life are not related, when tested at the 0.05 level of significance. C) residence after prison release and adjustment to civilian life are related, when tested at the 0.10 level of significance. D) residence after prison release and adjustment to civilian life are related, when tested at the 0.05 level of significance. E) residence after prison release and adjustment to civilian life are not related, when tested at the 0.10 and 0.05 level of significance.

1218.2) What is the critical value for this contingency table at the 0.01 level of significance? A) 9.488 B) 2.070 C) 11.345 D) 13.277

1219) The following table classifies an individual in two ways—by gender and by educational

choice. Chi-square Contingency Table Test for Independence No postsecondary

Community College

University

Total

Males

Female

Total

4.65

chi-square

.0977

p-value

Using the data from this MegaStat printout, you determine: A) gender and educational choices are not related, when tested at the 0.10 level of significance. B) gender and educational choices are not related, when tested at the 0.05 level of significance. C) gender and educational choices are related, when tested at the 0.10 level of significance. D) gender and educational choices are related, when tested at the 0.05 level of significance. E) gender and educational choices are not related, when tested at the 0.05 level of significance, but are related when tested at the 0.10 level of significance.

1220) The following table classifies an individual in two ways—by gender and by educational

choice. College Attended Gender

None

Two-Year

Four-Year

Total

Males

Female

Total

100

What is this two-way classification called? A) Goodness-of-fit test B) Frequency table C) No-load table D) Contingency table

1221) To analyze data cross-classified in a contingency table, how are the degrees of freedom

found? A) N - 1 B) Rows - Columns C) (Rows) × (Columns) D) (Rows - 1) × (Columns - 1)

1222) A sample of 100 production workers is obtained. The workers are classified by gender

(male, female) and by age (under 20, 20 - 29, 30 - 39 and 40 or over). How many degrees of freedom are there? A) 0 B) 3 C) 6 D) 5

1223) For a chi-square test involving a contingency table, suppose the null hypothesis is

rejected. We conclude that the two variables are: A) linear. B) curvilinear. C) not related. D) related.

1224) Which of the following can be used to test if two nominal variables or characteristics are

related? A) A contingency table B) A chi-square table C) An ANOVA table D) A scatter diagram

1225) A survey of the opinions of property owners about a street widening project was taken to

determine whether the resulting opinion was related to the distance of front footage. A randomly selected sample of 100 property owners was contacted and the results are shown below. Opinion Front-Footage

For

Undecided

Against

Under 45 feet

45-120 feet

Over 120 feet

1225.1) What kind of table is this classification? Determine the null and alternate hypotheses. A) Contingency; Ho: Opinions and property front-footage are independent; H1: Opinions

and property front-footage are related. B) Goodness-of-fit; Ho: Opinions and property front-footage are independent; H1: Opinions and property front-footage are related. C) Goodness-of-fit; Ho: Opinions and property front-footage are the same; H1: Opinions and property front-footage are different. D) Contingency; Ho: Opinions and property front-footage are related; H1: Opinions and property front-footage are independent.

1225.2) What is the computed value of chi-square? A) 7.89 B) 8.97 C) 6.78 D) 6.97 E) 6.89

1225.3) If the computed chi-square is 8.5, what is your decision at the 5% level of significance?

What is your decision at the 1% level of significance? A) Do not reject H0at either the 5% or 1% levels of significance; opinion and property frontage are independent. B) Reject Ho at the 5% level of significance, but not at the 1% level of significance. C) Reject Ho at the 1% level of significance, but not at the 5% level of significance. D) Reject Ho at both the 1% and 5% levels of significance; opinion and property frontage are related.

1225.4) If the computed chi-square is 8.5, what is your decision at the 10% level of significance? A) Reject H0; opinion and property front-footage are related. B) Accept H0; opinion and property front-footage are related. C) Reject H0; opinion and property front-footage are not related. D) Accept H0; opinion and property front-footage are not related.

1225.5) How many degrees of freedom are there? A) 2 B) 3 C) 4 D) 5

1225.6) What is the critical value at the 5% level of significance? A) 7.779 B) 9.488 C) 9.236 D) 11.070

1225.7) What is the critical value at the 10% level of significance? A) 7.779 B) 9.236 C) 9.488 D) 11.070

1225.8) What is the expected frequency for people who are undecided about the project and have

property front-footage between 45 and 120 feet? A) 2.2 B) 3.9 C) 5.0 D) 7.7

1225.9) What is the expected frequency for people who are in favour of the project and have less

than 45 feet of property foot-frontage? A) 10 B) 12 C) 35 D) 50

1225.10)

What is the expected frequency for people against the project and who have over 120 feet of property foot-frontage? A) 1.1 B) 3.9 C) 5.0 D) 5.5

1226) A survey of the opinions of property owners about a street widening project was taken to

Undecided

Against

Total

under 45 feet

45-120 feet

over 120 feet

Total

100

6.78

chi-square

.1477

p-value

Which of the following statements are correct? A) Property Front-footage and Opinion on the street widening are related when tested at the 0.10 level of significance. B) Property Front-footage and Opinion on the street widening are related when tested at the 0.05 level of significance. C) Property Front-footage and Opinion on the street widening are not related when tested at the 0.05 level of significance. D) Property Front-footage and Opinion on the street widening are not related when tested at the 0.20 level of significance. E) Property Front-footage and Opinion on the street widening are unrelated when tested at any level of significance.

1227) Recently, students in a marketing research class were interested in the driving behavior of

students. Specifically, the marketing students were interested if exceeding the speed limit was related to gender. They collected the following responses from 100 randomly selected students: Speeds

Does Not Speed

Males

Females

1227.1) The appropriate test to analyze the relationship between gender and speeding is: A) regression analysis. B) analysis of variance. C) contingency table analysis. D) goodness-of-fit. E) correlation analysis.

1227.2) The appropriate test statistic for the analysis is: A) F-statistic. B) t-statistic C) Chi-square statistic D) Z-statistic

1227.3) The null hypothesis for the analysis is: A) there is no relationship between gender and speeding. B) the correlation between gender and speeding is zero. C) as gender increases, speeding increases. D) the mean of gender equals the mean of speeding.

1227.4) The degrees of freedom for the analysis is: A) 1 B) 2 C) 3 D) 4 E) 5

1227.5) Using 0.05 as the significance level, what is the critical value for the test statistic? A) 3.841 B) 5.991 C) 7.815 D) 9.488 E) 0

1227.6) What is the value of the test statistic? A) 100 B) 9.89 C) 50 D) 4.94 E) 0

1227.7) Based on the analysis, what can be concluded? A) Gender and speeding are correlated. B) Gender and speeding are not related. C) Gender and speeding are related. D) The mean of gender equals the mean of speeding. E) No conclusion is possible.

1228) At a recent automobile show, a sample of 125 people produced the following results. Use

the 0.05 significance level to determine if there is a relationship between age and model preferred. Chi-square Contingency Table Test for Independence Sports

SUV

Luxury

Total

Under 30

30 to 50

over 50

Total

125

9.89

chi-square

.0423

p-value

1228.1) Based on the analysis above, what can be concluded? A) Buyer's age and car model preference are not related. B) Buyer's age and car model preference are related. C) The mean of age is the same as the mean of car model preference. D) No conclusion can be made.

1228.2) Based on the analysis above, what can be concluded if the significance level is 0.01? A) Buyer's age and car model preference are not related. B) Buyer's age and car model preference are related. C) The mean of age is the same as the mean of car model preference. D) No conclusion can be made.

1228.3) Use the 0.05 significance level and the p-value above to determine if there is a

relationship between age and model preferred. A) Reject the null hypothesis, there is a significant relationship between age and model preferred at the 5% level of significance. B) Unable to reject the null hypothesis, there is a significant relationship between age and model preferred at the 5% level of significance. C) Reject the null hypothesis, there is insufficient evidence to show a significant relationship between age and model preference. D) Unable to reject the null hypothesis, there is significant relationship between age and model preferred at the 5% level of significance.

1228.4) Use the 0.01 significance level and the p-value above to determine if there is a

relationship between age and model preferred. A) Reject the null hypothesis, there is a significant relationship between age and model preferred at the 1% level of significance. B) Unable to reject the null hypothesis, there is a significant relationship between age and model preferred at the 1% level of significance. C) Reject the null hypothesis, there is insufficient evidence to show a significant relationship between age and model preference at the 1% level of significance. D) Unable to reject the null hypothesis, there is insufficient evidence to show a significant relationship between age and model preference at the 1% level of significance.

1229) At a recent automobile show, a sample of 135 people produced the following results. Chi-square Contingency Table Test for Independence Sports

SUV

Luxury

Total

under 30

30 to 50

over 50

Total

135

12.20

chi-square

.0159

p-value

1229.1) Based on the analysis above, what can be concluded? Use the 0.05 significance level to

determine if there is a relationship between age and model preferred. A) Buyer's age and car model preference are not related. B) Buyer's age and car model preference are related. C) The mean of age is the same as the mean of car model preference. D) No conclusion can be made.

1229.2) Based on the analysis above, what can be concluded? Use the 0.01 significance level to

1230) If we wanted to see if tossing a die (a cube with the sides numbered one through six) had

an equal chance of showing each side or number, what statistical test should be applied? A) A chi-square goodness-of-fit test B) Difference between two means C) Contingency table analysis D) Single population proportion

1231) If an employee wanted to investigate the relationship between performance rating and

gender, what type of analysis should be used? A) A chi-square goodness-of-fit test B) Difference between two means C) Contingency table analysis D) Single population proportion

1232) At a recent car show, a sample of 125 people produced the following results. Calculate

the value of chi-square to determine if there is a relationship between age and model preferred. Age (in years)

Sports

SUV

Luxury

Total

under 30

30 to 50

over 50

125

A) 9.89, there is a significant relationship between age and model preferred at the 5%

level of significance. B) 9.99, there is a significant relationship between age and model preferred at the 5% level of significance. C) 8.89, there is insufficient evidence to show a significant relationship between age and model preference. D) 8.98, there is significant relationship between age and model preferred at the 5% level of significance.

1233) Following the COP21 summit, a sample of 200 people produced the following results.

Determine if age is related to a person's opinion on the success of the summit at addressing the "no more than + 1.50 C" temperature increase initiative. Not Enough

Good

Excellent

Total

under 20

20 to 40

40 to 60

Over 60

40 200

1233.1) What statistical test should be applied? A) A chi-square goodness-of-fit test B) Difference between two means C) Contingency table analysis D) Single population proportion

1233.2) What type of classification is this table? Determine the null and alternative hypothesis. A) Contingency; Ho: Opinions and Age are independent; H1: Opinions and Age are

related. B) Goodness-of-fit; Ho: Opinions and Age are independent; H1: Opinions and Age are related. C) Goodness-of-fit; Ho: Opinions and Age are the same; H1: Opinions and Age are different. D) Contingency; Ho: Opinions and Age are related; H1: Opinions and Age are independent.

1233.3) What is the value of the test statistic? A) 200 B) 36.41 C) 6 D) 2.5

1233.4) What are the degrees of freedom? A) 200 B) 193 C) 7 D) 6

1233.5) What is the decision rule at a significance level of 10%? A) Reject H0 in favour of H1 if the test statistic is > 9.236 B) Reject H0 in favour of H1 if the test statistic is > 10.645 C) Reject H0 in favour of H1 if the test statistic is > 11.070 D) Reject H0 in favour of H1 if the test statistic is > 12.592

1233.6) What is the decision rule at a significance level of 5%? A) Reject H0 in favour of H1 if the test statistic is > 9.236 B) Reject H0 in favour of H1 if the test statistic is > 10.645 C) Reject H0 in favour of H1 if the test statistic is > 11.070 D) Reject H0 in favour of H1 if the test statistic is > 12.592

1233.7) What is the decision rule at a significance level of 1%? A) Reject H0 in favour of H1 if the test statistic is > 13.388 B) Reject H0 in favour of H1 if the test statistic is > 15.033 C) Reject H0 in favour of H1 if the test statistic is > 15.086 D) Reject H0 in favour of H1 if the test statistic is > 16.812

1233.8) Based on the 10% level of significance what conclusions can be made? A) The opinion as to success of the summit and a person's Age are not related. B) The opinion as to success of the summit and a person's Age are related. C) The mean of the opinion on the success of the summit is the same as the mean of a

person's age. D) No conclusion can be made.

1233.9) Based on the 1% level of significance what conclusions can be made? A) The opinion as to success of the summit and a person's Age are not related. B) The opinion as to success of the summit and a person's Age are related. C) The mean of the opinion on the success of the summit is the same as the mean of a

person's age. D) No conclusion can be made.

1234) A survey of 1200 1st year students were asked which business major they were planning

on majoring in. The results are summarized between 6 popular majors to determine if each major was equally likely: ACC

FIN

H|R

MGT

MARK

OP/Research

225

175

225

180

245

150

1234.1) What kind of frequencies are the numbers: 225,175,225,180,245,150? A) Acceptance B) Critical value C) Expected D) Observed

1234.2) How many degrees of freedom are there? A) 1200 B) 1194 C) 6 D) 5

1234.3) What is the expected frequency? A) 1200 B) 1194 C) 200 D) 194

1234.4) What is the critical value at the 0.05 level of significance? A) 11.070 B) 3.841 C) 5.991 D) 9.236 E) 9.438

1234.5) What is the critical value at the 0.02 level of significance? A) 11.070 B) 13.388 C) 15.086 D) 9.236 E) 9.438

1234.6) What is the calculated value of chi-squared? A) 11.070 B) 13.388 C) 200 D) 34 E) 9.438

1234.7) What is your decision at the 1% level of significance? What is your decision at the 5%

level of significance? A) Reject Ho; Conclude student major is not equally likely at the 1% level of significance; also reject at the 5% level of significance. B) Reject Ho at the 1% level of significance but not at the 5% level of significance. C) Reject Ho at the 5% level of significance but not at the 1% level of significance. D) Accept Ho at both the 5% and 1% levels of significance. All majors are equally likely and differences are due to random chance.

Answer Key Test name: chapter 14 558) A 559) B 560) E 561) E 562) D 563) A 564) A 565) B 566) C 567) D 568) A 569) A 570) A 571) A 572) D 573) B 574) E 575) A 576) D 577) D 578) C 579) D 580) A 581) D 582) C 583) B 584) C 585) B 586) A 587) Section Break 587.1) D 587.2) A 587.3) A 587.4) C 587.5) B 587.6) D 587.7) D

587.8) D 587.9) E 588) B 589) C 590) A 591) A 592) C 593) B 594) A 595) B 596) A 597) B 598) C 599) D 600) A 601) B 602) C 603) D 604) A 605) A 606) D 607) D 608) A 609) A 610) A 611) B 612) A 613) D 614) C 615) C 616) Section Break 616.1) D 616.2) D 616.3) B 616.4) C 616.5) B 617) Section Break 617.1) A 617.2) E 617.3) A

617.4) E 617.5) B 617.6) A 618) C 619) A 620) B 621) A 622) A 623) C 624) B 625) B 626) C 627) Section Break 627.1) C 627.2) C 628) B 629) C 630) Section Break 630.1) E 630.2) C 631) E 632) D 633) D 634) B 635) D 636) A 637) Section Break 637.1) A 637.2) C 637.3) A 637.4) A 637.5) C 637.6) B 637.7) A 637.8) D 637.9) A 637.10) B 638) C 639) Section Break 639.1) C

639.2) C 639.3) A 639.4) A 639.5) A 639.6) B 639.7) C 640) Section Break 640.1) B 640.2) A 640.3) A 640.4) D 641) Section Break 641.1) A 641.2) B 642) A 643) C 644) A 645) Section Break 645.1) C 645.2) A 645.3) B 645.4) D 645.5) B 645.6) D 645.7) D 645.8) B 645.9) B 646) Section Break 646.1) D 646.2) D 646.3) C 646.4) A 646.5) B 646.6) D 646.7) A

Student name:__________ 1235) An index number is a percent that can measure the change from one period of time to

another in: A) Value. B) Price. C) Quantity. D) Volume. E) Value, price, quantity or volume.

1236) i. An index number is a percent that measures the change in price, quantity, value or

some other item of interest from one time to another. ii. An index of 239.2 and an index of 86.4 are actually percents. iii. All indexes have the same base, namely 2002, written 2002=100. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1237) i. An index of 239.2 and an index of 86.4 are actually percents.

ii. All indexes have the same base, namely 2002, written 2002 = 100. iii. The base period for one index might be 2002, while the base period for another index might be 1992. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1238) i. All indexes have the same base, namely 2002, written 2002 = 100.

ii. The base period for one index might be 2002, while the base period for another index might be 1977. iii. The base number for most indexes is 1. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are incorrect statements but (ii) is correct. D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1239) i. The base period for one index might be 2002 while the base period for another index

might be 1977. ii. The base number for most indexes is 1. iii. Most business and economic indexes are carried either to the nearest whole percent, such as 312 or 96, or to the nearest 10th of a percent, such as 97.5 and 178.6. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1240) i. The base number for most indexes is 1.

ii. Most business and economic indexes are carried either to the nearest whole percent, such as 312 or 96, or to the nearest 10th of a percent, such as 97.5 and 178.6. iii. Converting data to indexes makes it easier to compare the trend in a series composed of exceptionally large numbers. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1241) i. An index of 239.2 and an index of 86.4 are actually percents.

ii. The base period for one index might be 2002-100, while the base period for another index might be 1977. iii. Most business and economic indexes are carried either to the nearest whole percent, such as 312 or 96, or to the nearest 10th of a percent, such as 97.5 and 178.6. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1242) i. An index number is a percent that measures the change in price, quantity, value, or

some other item of interest from one time to another. ii. The base number for most indexes is 1. iii. Converting data to indexes makes it easier to compare the trend in a series composed of exceptionally large numbers. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1243) i. An index number is a percent that measures the change in price, quantity, value, or

some other item of interest from one time to another. ii. An Italian, G.R. Carli, has been credited with originating Fisher's Ideal Index. iii. Converting data to indexes makes it easier to compare the trend in a series composed of exceptionally large numbers. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1244) Listed below are the top-steel producing nations, in millions of tons, for the year 2004.

Express the amount produced by China, the European Union, Japan and Russia as an index, using the United States as a base. Nation

Amount (millions of tons)

China

197

European Union

144

Japan

103

United States

Russia

1244.1) What percent more steel does China produce than the United States? A) 197 B) 252.6 C) 152.6 D) 52.6 E) 47.4

1244.2) What percent more steel does the European Union produce than the United States? A) 184.6 B) 84.6 C) 15.4 D) 52.6 E) 47.4

1244.3) What percent more steel does Japan produce than the United States? A) 184.6 B) 84.6 C) 15.4 D) 52.6 E) 32.1

1245) The average weekly earnings (including overtime) in Canada since 2003 are given below. Year

Average Weekly Earnings

2003

$679.32

2004

688.31

2005

702.87

2006

725.51

2007

747.08

1245.1) Using 2003 as the base year, determine the index for 2004. A) 101.3 B) 1.3 C) 201.3 D) 103.5 E) 106.8

1245.2) Using 2003 as the base year, determine the index for 2005. A) 101.3 B) 1.3 C) 201.3 D) 103.5 E) 106.8

1245.3) Using 2003 as the base year, determine the index for 2006. A) 101.3 B) 1.3 C) 201.3 D) 103.5 E) 106.8

1246) If the average hourly earnings in mining in 2008 were $7.67 and for the most recent

month it was $14.90. What is the index of hourly earnings for the most recent month based on 2008? A) 100.0 B) 186.9 C) 51.5 D) 194.3 E) 151.5

1247) The Statistics Canada reported that the farm population dropped from 30.5 million in

1940 to 16.5 million in 1999. What is the index for 1999 based on 1940? A) 45.9 B) 103.0 C) 54.1 D) 78.7 E) 184.8

1248) Sean McCarthy earns $20,000 a year; John Nowak, $35,000. What is John's income as an

index using Sean's income as the base? A) 157.1 B) 75.0 C) 100.0 D) 57.1 E) 175.0

1249) The wholesale price of a straight back desk chair in 2019 was $20; in 2020, $23; and in

2021, $18. What were the indexes for 2019 and 2021 using 2020 = 100? A) 115.0 and 90.0 B) 1.15 and 0.9 C) 1150.0 and 900.0 D) 87.0 and 111.1 E) 87.0 and 78.3

1250) Data for selected vegetables purchased at wholesale prices for 2016 and 2021 are shown

below. 2016

2016

2021

Price

Qty

Price

Qty

Cabbage(kg)

$0.06

2,000

$0.05

1,500

Carrots(bunch)

0.10

200

0.12

200

Peas(kg)

0.20

400

0.18

500

Broccoli(each)

0.30

100

0.50

200

1250.1) What is the unweighted aggregate price index? A) 98.4 B) 107.0 C) 117.5 D) 128.8 E) 88.9

1250.2) What is Fisher's Ideal Index? A) 107.5 B) 102.6 C) 112.8 D) 103.2 E) 102.7

1250.3) What is the interpretation of the value index? A) Total value of purchases rose 10.3% B) Total value of purchases rose 18.5% C) Total value of purchases fell 1.6% D) Total value of purchases rose 8% E) Total value of purchases rose 15.6%

1250.4) What is the interpretation of Laspeyres' price index? A) Prices rose 98.4% B) Prices declined 1.6% C) Prices rose 7.0% D) Prices rose 8.0% E) Prices rose 15.6%

1250.5) What is Laspeyres' price index? A) 98.4 B) 107.0 C) 108.0 D) 117.5 E) 115.6

1250.6) What is Paasche's price index? A) 98.4 B) 107.0 C) 108.0 D) 117.5 E) 115.6

1251) i. Etienne Laspeyres developed a method in the latter part of the 19thcentury to determine

a weighted index using base-period weights. ii. If we are constructing a weighted index of the price of food for 2020 using the Laspeyres' method and 2002 = 100, we use the amounts consumed in the base period, q0, as weights. iii. The Laspeyres' method allows for a meaningful comparison of prices over time; however, if does not reflect changes in buying patterns over time. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1252) i. Etienne Laspeyres developed a method in the latter part of the 19thcentury to determine

a weighted index using base-period weights. ii. If we are constructing a weighted index of the price of food for 2000 using the Laspeyres' method and 1982-84 = 100, we use the amounts consumed in the base period, q0, as weights. iii. The Laspeyres' method changes in buying patterns over time. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1253) i. Etienne Laspeyres developed a method in the latter part of the 19thcentury to determine

a weighted index using base-period weights. ii. If we are constructing a weighted index of the price of food for 2020 using the Laspeyres' method and 2002 = 100, we use the price of food in the base period, q0, as weights. iii. The Laspeyres' method allows for a meaningful comparison of prices over time; however, if does not reflect changes in buying patterns over time. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1254) An index of clothing prices for 2014 based on 2000 is to be constructed. The prices for

2000 and 2014 and the quantity consumed in 2000 are shown below. Item

2015 Price

2015 Amount Sold

2021 Price

Dress (each)

$35

500

$65

Shoes(pair)

$40

1200

$90

Assuming that the number sold remained constant, i.e., the same number were sold in 2021 as in 2015, what is the weighted index of price for 2021 using 2015 as the base? A) 206.7 B) 214.5 C) 48.4 D) 46.6 E) 240.0

1255) An index of clothing prices for 2021 based on 2015 is to be constructed. The clothing

items considered are shoes and dresses. The information for prices and quantities for both years is given below. Use 2015 as the base period and 100 as the base value. Item

2015 Price

2015 Quantity

2021 Price

2021 Quantity

Dress (each)

$75

500

$85

520

Shoes(pair)

$40

1200

$45

1300

1255.1) Determine the simple average of the price indexes. A) 111.8 B) 112.9 C) 113.3 D) 112.5 E) 113.0

1255.2) Determine the Aggregate price index for 2021. A) 111.8 B) 112.9 C) 113.3 D) 112.5 E) 113.0

1255.3) Determine the Laspeyres' price index for 2021. A) 111.8 B) 112.9 C) 113.3 D) 112.5 E) 113.0

1255.4) Determine the Paasche price index for 2021. A) 111.8 B) 112.9 C) 113.3 D) 112.5 E) 113.0

1255.5) Determine the Fisher's ideal index for 2014. A) 111.8 B) 112.9 C) 113.3 D) 112.5 E) 113.0

1256) Prices and the number produced for selected agricultural items are: Item

Price

Production

2015

2021

2015

2021

What (bushel)

$2.00

$4.00

100

700

Eggs (dozen)

$0.30

$0.20

1000

800

Pork (cwt.)

$60.00

$70.00

110

Using the Laspeyres method, what is the price index for these items for 2021 (2015 = 100)? A) 42.5 B) 257.5 C) 127.9 D) 85.3 E) 117.1

1257) An index which compares current prices times current quantities to base period prices

times base period quantities called? A) Laspayres' Price Index B) Paasche Price Index C) Value Index D) Fisher's Ideal Index E) Special Purpose Index

1258) The number of items produced and the price per item for the Duffy Manufacturing

Company are: Price

Production

Item Produced

2019

2021

2019

2020

Shear pins (box)

10,000

9,000

Cutting compound (kg.)

600

200

Tie rods (each)

3,000

5,000

What is the value index of production for 2021 using 2019 as the base period? A) 115.2 B) 72.9 C) 110.6 D) 127.1 E) 114.9

1259) i. An index is a convenient way of comparing changes for different variables, i.e.,

average income and food prices. ii. No systematic approach to collecting and reporting data in index form was evident in North America until about 1900. iii. The CPI can be used in determining "real" income. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1260) i. No systematic approach to collecting and reporting data in index form was evident in

North America until about 1900. ii. The CPI can be used in determining "real" income. iii. Purchasing power of the dollar is determined by finding the inverse of the CPI. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1261) i. An index is a convenient way of comparing changes for different variables, i.e.,

average income and food prices. ii. The concept of real income is sometimes called deflated income. iii. Purchasing power of the dollar is determined by finding the inverse of the CPI. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1262) i. An index is a convenient way of comparing changes for different variables, i.e.,

average income and food prices. ii. The concept of real income is sometimes called deflated income. iii. Purchasing power of the dollar is the same as the CPI. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1263) i. Social security, old-age pensions, many apartment leases and many labour contracts are

tied to the change in the CPI. ii. Millions of employees in automobile, steel and other industries have their wages adjusted upward when the CPI increases. The specifics are in the management-union contracts. These clauses in the contracts are referred to as "cola clauses." iii. If two or more series of index numbers have the same year as the base period, then they can be compared directly. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1264) i. Millions of employees in automobile, steel and other industries have their wages

adjusted upward when the CPI increases. The specifics are in the management-union contracts. These clauses in the contracts are referred to as "cola clauses." ii. If two or more series of index numbers have the same year as the base period, then they can be compared directly. iii. When two or more series of index numbers to be compared do not have the same base period, we select a common base period for all series. Then we use the respective base numbers as the denominators and convert each base to the new base. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1265) i. If two or more series of index numbers have the same year as the base period, then they

can be compared directly. ii. When two or more series of index numbers to be compared do not have the same base period, we select a common base period for all series. Then we use the respective base numbers as the denominators and convert each base to the new base. iii. Canada pension plan payments and old age security pensions are periodically adjusted based on the Consumer Price Index. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1266) i. When two or more series of index numbers to be compared do not have the same base

period, we select a common base period for all series. Then we use the respective base numbers as the denominators and convert each base to the new base. ii. Canada pension plan payments and old age security pensions are periodically adjusted based on the Consumer Price Index. iii. The largest component of the Canadian CPI is Food. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1267) i. Canada pension plan payments and old age security pensions are periodically adjusted

based on the Consumer Price Index. ii. The largest component of the Canadian CPI is Food. iii. Besides measuring change in the prices of goods and services, the consumer price indexes have a number of other applications. The CPI is used to determine real disposable personal income, deflate sales or other series, find the purchasing power of the dollar and establish cost of living increases. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1268) i. The largest component of the Canadian CPI is Food.

ii. Besides measuring change in the prices of goods and services, the consumer price indexes have a number of other applications. The CPI is used to determine real disposable personal income, deflate sales or other series, find the purchasing power of the dollar and establish cost of living increases. iii. The concept of real income is sometimes called deflated income or income expressed in constant dollars and the CPI is called the deflator. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1269) i. Besides measuring change in the prices of goods and services, the consumer price

indexes have a number of other applications. The CPI is used to determine real disposable personal income, deflate sales or other series, find the purchasing power of the dollar and establish cost of living increases. ii. The concept of real income is sometimes called deflated income or income expressed in constant dollars and the CPI is called the deflator. iii. To deflate sales, the actual sales are multiplied by the wholesale price index and the result multiplied by 100. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1270) i. The concept of real income is sometimes called deflated income or income expressed in

constant dollars and the CPI is called the deflator. ii. To deflate sales, the actual sales are multiplied by the wholesale price index and the result multiplied by 100. iii. The CPI serves only one major function: as an economic indicator of the rate of inflation. A) (i) is a correct statement, but (ii) and (iii) are statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1271) i. To deflate sales, the actual sales are multiplied by the wholesale price index and the

result multiplied by 100. ii. The CPI serves only one major function: as an economic indicator of the rate of inflation. iii. To construct a special-purpose index designed to measure general business activity, the weights are based on the judgments of the statistician and assigned to each series. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (iii) is a correct statement, but not (i) or (ii). E) (i), (ii), and (iii) are all false statements

1272) i. The CPI serves only one major function: as an economic indicator of the rate of

inflation. ii. To construct a special-purpose index designed to measure general business activity, the weights are based on the judgments of the statistician and assigned to each series. iii. The Consumer Price Index measures the change in prices of a fixed market basket of goods and services from one period to another. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1273) i. To construct a special-purpose index designed to measure general business activity, the

weights are based on the judgments of the statistician and assigned to each series. ii. The Consumer Price Index measures the change in prices of a fixed market basket of goods and services from one period to another. iii. The CPI is not just one index, but includes a large number of groups, subgroups and selected items, such as a food index, a transportation index and a shelter index. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1274) i. The Consumer Price Index measures the change in prices of a fixed market basket of

goods and services from one period to another. ii. The CPI is not just one index, but includes a large number of groups, subgroups and selected items, such as a food index, a transportation index and a shelter index. iii. The Consumer Price Index is based on more than 600 separate goods and services used by most urban and rural families. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1275) i. The CPI is not just one index, but includes a large number of groups, subgroups and

selected items, such as a food index, a transportation index and a shelter index. ii. The Consumer Price Index is based on more than 600 separate goods and services used by most urban and rural families. iii. One function of CPI is to allow consumers to determine the degree to which their purchasing power is being eroded by price increases and as such, it is a metre stick for revising wages, pensions and other income payments to keep pace with changes in prices. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1276) i. Millions of employees in automobile, steel and other industries have their wages

adjusted upward when the CPI increases. The specifics are in the management-union contracts. These clauses in the contracts are referred to as "cola clauses." ii. When two or more series of index numbers to be compared do not have the same base period, we select a common base period for all series. Then we use the respective base numbers as the denominators and convert each base to the new base. iii. The largest component of the Canadian CPI is Food. A) (i), (ii), and (iii) are all correct statements B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements

1277) i. Social security, old-age pensions, many apartment leases and many labour contracts are

tied to the change in the CPI. ii. Millions of employees in automobile, steel and other industries have their wages adjusted upward when the CPI increases. The specifics are in the management-union contracts. These clauses in the contracts are referred to as "cola clauses." iii. To deflate sales, the actual sales are multiplied by the wholesale price index and the result multiplied by 100. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1278) The CPI for "educational books and supplies" in July of 2021 was 295.1 (2002 = 100).

Interpret this index. A) There was no significant increase in the price of "educational books and supplies". B) The price of "educational books and supplies" increased 195.1%. C) If the average price of a textbook in 2002-100 was $25.00, the CPI for "educational books and supplies" would predict that the price of the textbook in July 2021 would be $73.78. D) If the average price of a textbook in 2002 was $25.00, the CPI for "educational books and supplies" would predict that the price of the textbook in July 2021 would be $48.78. E) The price of "educational books and supplies" decreased 195.1%.

1279) What component(s) does the CPI include? A) Recreation and Education B) Food C) Shelter D) Clothing E) Recreation and Education, Food, Shelter, and Clothing.

1280) The CPI for "personal computers and peripheral equipment" in July of 2021 was 29.3

(2002 = 100). Interpret this index. A) There was no significant increase in the price of "personal computers and peripheral equipment" B) The price of "personal computers and peripheral equipment" increased 29.3%. C) The price of "personal computers and peripheral equipment" decreased 70.7%. D) If the average price of a computer in 2002 was $879.00, the CPI for "personal computers and peripheral equipment" would predict that the price of a computer in July 2021 would be $3,000.00. E) The price of "personal computers and peripheral equipment" decreased 29.3%.

1281) Real income is computed by: A) dividing money income by the CPI and multiplying by 100. B) dividing the CPI by money income and multiplying by 100. C) multiplying money income by the CPI. D) subtracting the CPI from money income. E) dividing a dollar by the CPI and multiplying by 100.

1282) As chief statistician for the municipality, you want to compute and publish every year a

special-purpose index, which you plan to call Index of Municipal Business Activity. Three series seem to hold promise as the basis for the index; namely, the price of wheat, the number of new automobiles sold and the rate of money turnover for the municipality (published by a local bank). Arbitrarily you decide that money turnover should have a weight of 60 percent; number of new automobiles sold, 30 percent; and the price of wheat, 10 percent. Price of Wheat

Number of Autos

Rate of Money Turnover

2017

$2.00

10000

2021

$5.00

8000

120

What is the Index of Municipal Business Activity for 2017 (the base year) and for 2021? A) 100 for 2017, 139 for 2021 B) 139 for 2017, 100 for 2021 C) 100 for 2017, 61 for 2021 D) 100 for 2017, 100 for 2021 E) 100 for 2017, 160 for 2021

1283) The Consumer Price Index in June 2021 was 248.4 (2002 = 100). What does this indicate

about prices from 2002 to June 2021? A) Rose 248.4% B) Rose 548.4% C) Rose 148.4% D) Declined 148.4% E) Declined 248.4%

1284) Below is Jim Walker's income for 2019 and 2021. Year

Income ($)

CPI (2010 - 12 = 100)

2019

17000

107.62

2021

37000

172.2

What was Jim's real income for 2021? A) $17,000 B) $27,000 C) $15,799 D) $21,487 E) $37,000

1285) The take home pay of an employee working in an urban area for 2010 and 2021 are: Year

Take Home Pay

2010

$5,000

2021

$13,200

If the CPI rose from 70 in 2010 to 172.2 in 2021 (2002 = 100), what was the "real" take home pay of the employee in 2021? A) $5,000 B) $7,143 C) $11,200 D) $7,666 E) $13,200

1286) How is the purchasing power of the dollar computed? A) ($1/CPI) (100) B) ($1 - CPI) (100) C) ($1 × CPI) (100) D) (CPI/$1) (100) E) ($1 + CPI) (100)

1287) If the Consumer Price Index is 172.2 (2002 = 100), what is the purchasing power of the

dollar? A) B) C) D) E)

$1.00 $0.33 $0.58 $0.50 $0.72

1288) The take-home pay of Jon Greene and the CPI for 2015 and 2022 are: Year

Take-Home Pay

CPI 2002=100

2015

35000

102.8

2022

41200

111.5

What was Jon's real income in 2015? A) $34,046.69 B) $34,500.00 C) $59,880.00 D) $41,200.00

1289) The take-home pay of Jon Greene and the CPI for 2015 and 2022 are: Year

Take-Home Pay

CPI 2002=100

2015

35000

102.8

2022

65000

111.5

What was Jon's real income in 2022? A) $34,046.69 B) $58,295.96 C) $59,880.00 D) $72,475.00 E) $57,988.24

1290) The take-home pay of Jon Greene and the CPI for 2015 and 2022 are: Year

Take-Home Pay

CPI 2002=100

2015

35000

102.8

2022

41200

111.5

What was Jon's real income in 2022? A) $34,046.69 B) $58,295.96 C) $39,650.00 D) $36,950.67 E) $41,200.00

1291) The take-home pay of Jon Greene and the CPI for 2015 and 2022 are: Year

Take-Home Pay

CPI 2002=100

2015

35000

102.8

2022

70000

111.5

What was Jon's real income in 2022? A) $69,650.00 B) $58,295.96 C) $39,650.00 D) $78,050 E) $62,780.27

1292) The take-home pay of Jon Greene and the CPI for 2018 and 2022 are: Year

Take-Home Pay

CPI 2002=100

2018

35000

102.8

2022

45000

111.5

What was Jon's real income in 2022? A) $50,175.00 B) $38,295.96 C) $39,650.00 D) $40,358.74 E) $42,780.27

1293) The following table shows the average earnings by gender of Canadian workers. Year

Women

Men

2014

23900

37400

2015

24200

37800

2016

24900

39000

2017

25100

39100

2018

25300

38900

2019

25800

41100

2021

26200

41300

2022

26800

41900

The changes in earnings for men and women are to be compared. Unfortunately, the base period of 2014 is different for the two groups.

1293.1) Determine the average earnings increase for both men and women over the period 2014

to 2018. A) Women's earnings increased by 5.9% and men's earnings increased by 4.0%. B) Women's earnings increased by 7.9% and men's earnings increased by 9.9%. C) Women's earnings increased by 9.6% and men's earnings increased by 11.4%. D) Women's earnings increased by 9.6% and men's earnings increased by 10.4%. E) Women's earnings increased by 12.1% and men's earnings increased by 12%.

1293.2) Determine the average earnings increase for both men and women over the period 2014

to 2022. A) Women's earnings increased by 12.1% and men's earnings increased by 12.0%. B) Women's earnings increased by 7.9% and men's earnings increased by 9.9%. C) Women's earnings increased by 9.6% and men's earnings increased by 10.4%. D) Women's earnings increased by 12.0% and men's earnings decreased by 12.1%. E) Women's earnings increased by 12.6% and men's earnings increased by 10.4%.

1293.3) Determine the average earnings increase for both men and women over the period 2014

to 2017. A) Women's earnings increased by 5% and men's earnings increased by 4.5%. B) Women's earnings increased by 7.9% and men's earnings increased by 9.9%. C) Women's earnings increased by 9.6% and men's earnings increased by 10.4%. D) Women's earnings increased by 9.6% and men's earnings decreased by 10.4%. E) Women's earnings increased by 5.9% and men's earnings increased by 4.0%.

1293.4) Determine the average earnings increase for both men and women over the period 2014

to 2019. A) Women's earnings increased by 12.1% and men's earnings increased by 12.0%. B) Women's earnings increased by 7.9% and men's earnings increased by 9.9%. C) Women's earnings increased by 9.6% and men's earnings increased by 10.4%. D) Women's earnings increased by 9.6% and men's earnings decreased by 10.4%. E) Women's earnings increased by 5.9% and men's earnings increased by 4.0%.

1294) In 2000, an executive earned $100,000. In 2009, the executive earned $125,000. The CPI

in 2000 was 172.2, and the CPI in 2009 was 214.537. Using the CPI base, 1992 = 100, what was the real income in 2009? A) $58,265 B) $58,072 C) $58,000 D) $58,999

1295) In 2000, an executive earned $100,000. In 2009, the executive earned $125,000. The CPI

in 2000 was 172.2, and the CPI in 2009 was 214.537. Using the CPI base, 1992 = 100, what was the real income in 2000? A) $58,265 B) $58,072 C) $58,000 D) $58,999

1296) In 2000, an executive earned $100,000. In 2009, the executive earned $125,000. The CPI

in 2000 was 172.2, and the CPI in 2009 was 214.537. Using the CPI base, 1992 = 100, what was the increase in real income from 2000 to 2009? A) $193 B) $139 C) $580 D) $173

1297) The 2009 CPI was 214.537 (1992 = 100). What is the purchasing power of the dollar

relative to the base? A) $0.47 B) $0.74 C) $0.44 D) $0.56

1298) The 2001 CPI was 171.1 (1992 = 100). What is the purchasing power of the dollar

relative to the base? A) $0.58 B) $0.74 C) $0.44 D) $0.56

1299) The Consumer Price Index (1992 = 100) reports a CPI in August 2010 for Energy as

212.372. What is the percentage change in the price of energy compared to the base? A) Increased 112.372 percent B) Decreased 112.372 percent C) Increased 212.372 percent D) Decreased 212.372 percent

1300) The Consumer Price Index (1992 = 100) reports a CPI in August 2010 for Rent of Shelter

as 239.115. What is the percentage change in the price of Rent of Shelter compared to the base? A) Increased 139.115 percent B) Decreased 139.115 percent C) Increased 239.115 percent D) Decreased 239.115 percent

1301) If the Laspeyres index is 140.78 and the Paasche index is 98.01, what is Fisher's ideal

index? A) B) C) D)

117.144 117.46 137.22 173.14

1302) If the Laspeyres index is 111.95 and the Paasche index is 122.58, what is Fisher's ideal

index? A) B) C) D)

117.144 13722 137.22 173.14

1303) If the Laspeyres index is 135.41 and the Paasche index is 145.34, what is Fisher's ideal

index? A) B) C) D)

117.144 13722 137.22 140.29

1304) The following data was collected on mutual fund prices. Shares in 2019

Price in 2019

Shares in 2022

Price in 2022

Cash

100

$1.00

300

$1.00

Bonds

300

$10.00

350

$12.00

Stocks

600

$25.00

1000

$40.00

1304.1) Compute value index to compare mutual fund prices in 2022 to 2019. A) 245.86 B) 154.51 C) 153.04 D) 147.22

1304.2) Compute the Paasche price index to compare mutual fund prices in 2022 to 2019. A) 245.86 B) 154.51 C) 153.04 D) 147.22

1304.3) Compute the Laspeyres price index to compare mutual fund prices in 2019 to 2022. A) 245.86 B) 154.51 C) 153.04 D) 147.22

1304.4) Compute a simple aggregate index comparing mutual fund prices in 2021 to mutual fund

prices in 2022. A) 245.86 B) 154.51 C) 153.04 D) 147.22

1305) The following data was collected comparing car prices and quantity sold (thousands). Car size

Number sold in 2018

Average Price in 2018

Number sold in 2020

Average price in 2020

Compact

300

$15,000

500

$16,000

Mid size

450

$20,000

350

$25,000

Large

100

$25,000

$35,000

1305.1) Compute the Paasche price index to compare car prices in 2018 to 2020. A) 115.93 B) 122.19 C) 126.67 D) 147.22

1305.2) Compute the Laspeyres price index to compare car prices in 2018 to 2020. A) 155.93 B) 122.19 C) 126.67 D) 147.22

1305.3) Compute the simple aggregate index to compare car prices in 2018 to 2020. A) 155.93 B) 122.19 C) 126.67 D) 147.22

1306) The Consumer Price Index was 122.8 (2002 = 100) for Canada All Items in 2022, what

was the purchasing power of the dollar? A) $1.00 B) $0.33 C) $0.58 D) $0.81 E) $0.72

1307) The Consumer Price Index was 122.8 (2002 = 100) for Canada All Items in 2022, what

was the purchasing power of the dollar? A) $1.00 B) $0.33 C) $0.58 D) $0.81 E) $0.72

1308) During the majority of the pandemic there was considerable pressure put on the prices of

groceries as a result of inflation and supply chain holdups. The following tables provides a summary of a sample of these price and quantity changes from 2020 through 2022: P2020

Q2020

P2022

Q2022

Bannas

0.57

2200

0.92

1850

Carrots

2.25

1985

3.55

2000

Ground Beef

11.25

4500

16.75

4100

Bread

3.75

6500

4.99

6400

Milk

3.99

8000

5.25

10000

1308.1) Using an unweighted index calculation, find the aggregate price index for the groceries

from 2020 to 2022. A) 146.5 B) 144.2 C) 143.7 D) 141.1 E) 140.6

1308.2) Similar to the computation of the Consumer price index find the Laspeyres price index

for 2020 to 2022. A) 146.5 B) 144.2 C) 143.7 D) 141.1 E) 140.6

1308.3) The calculation which calculates the movement in the economy is the Value index.

Compute the value index from 2020 to 2022. A) 146.5 B) 144.2 C) 143.7 D) 141.1 E) 140.6

1308.4) The Paache price index uses current year quantities as the weights. Calculate the Paache

price index. A) 146.5 B) 144.2 C) 143.7 D) 140.1 E) 140.6

1308.5) Calculate the Fisher's ideal index. A) 146.5 B) 144.2 C) 143.7 D) 140.6 E) 140.1

1308.6) Determine the value of the average of price relatives. A) 146.5 B) 144.2 C) 143.7 D) 140.6 E) 140.1

Answer Key Test name: chapter 15 647) E 648) B 649) C 650) C 651) C 652) D 653) A 654) C 655) A 656) Section Break 656.1) C 656.2) B 656.3) E 657) Section Break 657.1) A 657.2) D 657.3) E 658) D 659) C 660) E 661) E 662) Section Break 662.1) D 662.2) B 662.3) E 662.4) B 662.5) A 662.6) B 663) A 664) B 665) C 666) B 667) Section Break 667.1) B 667.2) E 667.3) B 667.4) B

667.5) B 668) E 669) C 670) D 671) A 672) A 673) A 674) B 675) A 676) A 677) A 678) B 679) C 680) D 681) B 682) A 683) D 684) D 685) A 686) A 687) A 688) B 689) B 690) B 691) E 692) C 693) A 694) A 695) C 696) D 697) D 698) A 699) C 700) A 701) B 702) D 703) E 704) D 705) Section Break 705.1) A

705.2) A 705.3) A 705.4) B 706) A 707) A 708) A 709) A 710) A 711) A 712) A 713) B 714) A 715) D 716) Section Break 716.1) A 716.2) B 716.3) C 716.4) D 717) Section Break 717.1) A 717.2) B 717.3) C 718) D 719) D 720) Section Break 720.1) B 720.2) D 720.3) C 720.4) D 720.5) D 720.6) A

Student name:__________ 1309) Economic periods of prosperity followed by recession are described as: A) Secular trend. B) Seasonal variation. C) Cyclical variation. D) Predictable variation. E) Irregular variation.

1310) What is variation within a year, such as high sales at Christmas and Easter and low sales

in January, called? A) Secular trend. B) Seasonal variation. C) Cyclical variation. D) Predictable variation. E) Irregular variation.

1311) The merchants in Abbotsford, BC suffered flood damage in November 2021. Stores were

closed for remodeling for months. What is this type of variation in sales called? A) Secular trend. B) Seasonal variation. C) Cyclical variation. D) Predictable variation. E) Irregular variation.

1312) Since a ski resort does most of its business in the winter, what is the major source of

variation in income due to? A) Secular trend. B) Seasonal variation. C) Cyclical variation. D) Predictable variation. E) Irregular variation.

1313) If the exports ($ millions) for the period 2017 through 2021 were $878, $892, $864,

$870, and $912 respectively. What are these values called? A) Moving average. B) Linear trend equation. C) Logarithmic trend equation. D) Time series. E) Secular Trend.

1314) What is the long-term behavior of a variable over an extended period of time called? A) Secular trend B) Seasonal variation C) Cyclical variation D) Irregular or variation E) Predictable variation.

1315) A time series is a collection of data that: A) records past performance. B) records future performance. C) has seasonality removed. D) has irregular variation removed. E) is limited to yearly data.

1316) Why are long range predictions considered essential to managing a firm? A) To develop plans for possible new plants. B) To have raw materials available for future demand C) To develop plans for future financing. D) To have enough staff for future needs. E) To develop plans for possible new plants and future financing, to have raw materials

available for future demands and to have enough staff for future needs.

1317) Which one of the following is not a component of a time series? A) Secular trend B) Moving average C) Seasonal variation D) Irregular variation E) Cyclical variation

1318) What is the correct order of events in a typical business cycle? A) Prosperity, recession, depression, and recovery B) Depression, recovery, recession, and prosperity C) Recovery, depression, prosperity, and recession D) Recession, recovery, prosperity, and depression E) Recession, depression, and regression

1319) The events that followed the outbreak of Covid-19 exerted an impact on the economy that

could be classified as: A) Secular trend. B) Irregular variation. C) Predictable variation. D) Seasonal variation. E) Cyclical variation.

1320) What time series component was exemplified during the 1980s when the World economy

enjoyed a period of prosperity? A) Irregular B) Cyclical C) Trend D) Seasonal E) Predictable variation.

1321) i. Long-term forecasts are usually from one year to more than 10 years into the future.

ii. A forecast is considered necessary in order to have the raw materials, production facilities, and staff available to meet estimated future demands. iii. Many business and economic time series have a recurring seasonal pattern. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1322) i. A time series is a collection of data recorded over a period of time, usually monthly,

quarterly, or yearly. ii. Episodic and residual variations can be projected into the future. iii. A forecast is considered necessary in order to have the raw materials, production facilities, and staff available to meet estimated future demands. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1323) i. Many business and economic time series have a recurring seasonal pattern.

ii. One component of a time series is cyclical variation. An example of cyclical variation is the business cycle that consists of periods of prosperity followed by periods of recession, depression and recovery. iii. Irregular variations can be projected into the future. A) (i), (ii) and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1324) i. One component of a time series is the secular trend that is the smooth movement of a

series over a short period of time, such as a few months or quarters. ii. Many business and economic time series have a recurring seasonal pattern. iii. One component of a time series is cyclical variation. An example of cyclical variation is the business cycle that consists of periods of prosperity followed by periods of recession, depression, and recovery. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1325) i. A forecast is considered necessary in order to have the raw materials, production

facilities, and staff available to meet estimated future demands. ii. One component of a time series is the secular trend that is the smooth movement of a series over a short period of time, such as a few months or quarters. iii. Many business and economic time series have a recurring seasonal pattern. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1326) i. Long-term forecasts are usually from one year to more than 10 years into the future.

ii. A forecast is considered necessary in order to have the raw materials, production facilities, and staff available to meet estimated future demands. iii. One component of a time series is the secular trend that is the smooth movement of a series over a short period of time, such as a few months or quarters. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1327) i. A time series is a collection of data recorded over a period of time, usually monthly,

quarterly, or yearly. ii. Long-term forecasts are usually from one year to more than 10 years into the future. iii. A forecast is considered necessary in order to have the raw materials, production facilities, and staff available to meet estimated future demands. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1328) For an annual time series extending from 2013 through 2021, how many years would be

lost in a five-year moving average? A) 2 at the start and 1 at the end. B) 1 at the start and 1 at the end. C) 2 at the start and 0 at the end. D) 0 at the start and 2 at the end. E) 2 at the start and 2 at the end.

1329) How can you describe the moving average method? A) Useful in smoothing out a time series. B) Used in measuring seasonal fluctuations. C) A technique which does not result in a trend line equation. D) A method for identifying a trend. E) A method for identifying a trend, but does not result in a trend line equation, is useful

in smoothing out a time series and measuring seasonal fluctuations.

1330) For a three-year moving average, how many values will be lost at the beginning and end

of the time series? A) 0 at the start and 2 at the end B) 3 at the start and 0 at the end C) 1 at the start and 1 at the end D) 0 at the start and 3 at the end E) 2 at the start and 0 at the end

1331) i. The moving average method merely smooths out the fluctuations in the data.

ii. The moving average method averages out cyclical ( C) and irregular ( I) components. iii. To apply the moving average method to a time series, the data should follow a linear trend and have a definite rhythmic pattern of fluctuations that repeat (say, every three years). A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1332) i. The moving average method averages out cyclical ( C) and irregular ( I) components.

ii. To apply the moving average method to a time series, the data should follow a linear trend and have a definite rhythmic pattern of fluctuations that repeat (say, every three years). iii. Sales, production and other economic and business series usually have periods of oscillation that are of equal length or identical amplitudes. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1333) i. The moving average method merely smooths out the fluctuations in the data.

1334) i. The moving average method merely smooths out the fluctuations in the data.

ii. The moving average method averages out cyclical ( C) and irregular ( I) components. iii. Sales, production and other economic and business series usually have periods of oscillation that are of equal length or identical amplitudes. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1335) The following linear trend equation was developed for annual sales from 2015 to 2021

with 2015 the base or zero year. ŷ = 500 + 60 t ($000). What are the estimated sales for 2025 ($000)? A) $500 B) $560 C) $600 D) $1,040 E) $1,100

1336) The following linear trend equation was developed for the annual sales of the Jordan

Manufacturing Company. ŷ = 500 + 60 t ($000). How much are sales increasing? A) $60,000 per year B) $6,000 per month C) $500,000 per year D) $6,000 per year E) $500 per month

1337) If the least squares equation for sales data is ŷ = 10 + 1.3 t ($ millions), with t = 0 in

2015, what is the value of t and the forecast for 2022? A) t = 6, y = 17.8 B) t = 0, y = 10.0 C) t = 7, y = 19.1 D) t = 10, y = 0.0 E) t = 7, y = 9.1

1338) If you have annual data for 2019 to 2022 and want to code the years for the calculation of

the trend, what should you code the year 2019? A) 0 B) 1 C) 91 D) -6 E) -13

1339) In the linear trend equation, how is the average change in the dependent variable

represented for every unit change in time? A) a B) b C) t D) ŷ E) r

1340) For a time series beginning with 1988 and extending up to 2021, which year would be

coded with a one when using the coded method? A) 1986 B) 1988 C) 1989 D) 1998 E) 1996

1341) A linear trend equation is used to represent time series values when the dependent data

are changing by equal? A) Percents B) Proportions C) Amounts D) Rights E) Exponents

1342) What is a disadvantage of estimating a trend line equation by "eye-balling" the best

fitting line to a scatter diagram? A) Provides quick approximations B) Is subject to human error C) Provides accurate forecasts D) Is too difficult to calculate E) Requires graph paper

1343) i. In a time series analysis, the letter "a" in the linear trend equation, is the value of when

t = 0. ii. In the linear trend equation, the letter "b" is the average change each change of one unit (either increase or decrease) in y. iii. In the linear trend equation, t is any value that corresponds with a time period, (i.e. month or quarter. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1344) i. In the linear trend equation, the letter "b" is the average change in t for each change of

one unit (either increase or decrease) in y. ii. In the linear trend equation, t is any value that corresponds with a time period, i.e., month or quarter. iii. The least squares method of computing the equation for a straight line going through the data of interest gives the "best fitting" line. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1345) i. In the linear trend equation, t is any value that corresponds with a time period, i.e.,

month or quarter. ii. The least squares method of computing the equation for a straight line going through the data of interest gives the "best fitting" line. iii. If the sales, production or other data over a period of time tend to approximate a straightline trend, the equation developed by the least squares method cannot be used to forecast sales for a future period. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1346) i. If the sales, production or other data over a period of time tend to approximate a

straight-line trend, the equation developed by the least squares method cannot be used to forecast sales for a future period. ii. A straight-line trend equation is used to represent the time series when it is believed that the data is increasing (or decreasing) by equal amounts, on the average, from one period to another. iii. If the past data approximates a straight line, the equation used is = a + bt, where a is they-intercept and b is the slope of the line. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1347) i. In the linear trend equation, the letter "b" is the average change in t for each change of

one unit (either increase or decrease) in y. ii. The least squares method of computing the equation for a straight line going through the data of interest gives the "best fitting" line. iii. A straight-line trend equation is used to represent the time series when it is believed that the data is increasing (or decreasing) by equal amounts, on the average, from one period to another. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1348) i. In a time series analysis, the letter "a" in the linear trend equation, is the value of when

t = 0. ii. In the linear trend equation, t is any value that corresponds with a time period, i.e., month or quarter. iii. If the sales, production or other data over a period of time tend to approximate a straightline trend, the equation developed by the least squares method cannot be used to forecast sales for a future period. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1349) i. In the linear trend equation, t is any value that corresponds with a time period, i.e.,

month or quarter. ii. A straight-line trend equation is used to represent the time series when it is believed that the data is increasing (or decreasing) by equal amounts, on the average, from one period to another. iii. If the past data approximates a straight line, the equation used is = a + bt, where a is they-intercept and b is the slope of the line. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1350) What is the forecast for year 9? Data: Coded year, t

Pass(000)

3.3

4.1

4.9

6.4

9.0

12.8

16.9

Regression Analysis

Liner r2 Adjusted r2 r Std. Error

1.663

observations

Predictor variable

Pass(000)

is the dependent variable

ANOVA table Source

Regression

138.6175

1 138.6175

Residual

13.8225

Total

152.44

Regression output

Confidence interval

variables

coefficients

intercept

-0.7

2.225

std. error

0.3142

p-value

50.14 9.00E-04

2.7645

t ( df=5)

pvalue

95% lower

95% upper

0.0009 1.4173

3.0327

Predicted values for: Pass(000) 95% Confidence 95% Interval Prediction Interval t

Predicted

lower

upper

lower

upper Leverage 1.036

A) B) C) D) E)

20.725 20.025 17.100 28.122 19.325

1351) Given the trend equation ŷ = 25 + 0.6t (t = 0 in 2020), what would be the forecast value

for 2024? A) 2.4 B) 28.0 C) 3.0 D) 32.0 E) 27.4

1352) Given a linear time series trend, = - 5.2 + 3.1t, what is the forecast for 2025 if the t = 0 in

2017? A) B) C) D) E)

22.7 33.1 30.0 21.7 19.6

1353) Listed below is the net sales in $ million for Home Depot Inc., and its subsidiaries from

2014 to 2022. Year

Net Sales ($million)

2014

15470

2015

19535

2016

24156

2017

30219

2018

38434

2019

45738

2020

53553

2021

58247

2022

64816

1353.1) Using the printout below, what are the estimated sales for 2023? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $77,690.9 Million $84,154.7 Million $103,546.4 Million $71,227.0 Million

1353.2) Using the printout below, what are the estimated sales for 2024? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $77,690.9 Million $84,154.7 Million $103,546.4 Million $71,227.0 Million

1353.3) Using the printout below, what are the estimated sales for 2026? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $477,690.9 Million $84,154.7 Million $103,546.4 Million $71,227.0 Million

1353.4) Using the printout below, what are the estimated sales for 2025? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $477,690.9 Million $84,154.7 Million $103,546.4 Million $71,227.0 Million

1353.5) Using the printout below, what are the estimated sales for 2027? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $97,082.5 Million $84,154.7 Million $103,546.4 Million $71,227.0 Million

1353.6) Using the printout below, what are the estimated sales for 2028? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $97,082.5 Million $84,154.7 Million $103,546.4 Million $71,227.0 Million

1353.7) Using the printout below, what are the estimated sales for 2029? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $97,082.5 Million $116,464.2 Million $103,546.4 Million $110,010.3 Million

1353.8) Using the printout below, what are the estimated sales for 2030? Regression output

A) B) C) D) E)

variables

coefficients

Intercept

13,052.0222

6,463.8833

$90,618.6 Million $97,082.5 Million $116,474.2 Million $103,546.4 Million $110,010.3 Million

1354) The general equation for the logarithmic trend equation is log = A) Ln a + Ln b(t) B) Ln at Ln b( t) C) at b( t) D) ab( t) b E) at

1355) How will data which increases (or decreases) by equal percents appear when plotted on

graph paper having an arithmetic scale? A) Straight line B) Linear C) Curvilinear D) Parabolic E) Discontinuous

1356) Which of the following is true for the exponential equation? A) Ln a = SLn ŷ/ n B) Ln ŷ = Ln a + tLn b C) Ln b = S( XLn)/ t2 D) Ln ŷ = Ln a + bLn t E) ŷ = a + bt

1357) A logarithmic straight-line trend equation should be used for forecasts when the time

series is increasing by? A) Equal amounts B) Increasing percents C) Increasing amounts D) Increasing or decreasing percents E) Constant percents

1358) If the data appears to be increasing exponentially and we wish to forecast number of

passengers for year 9, we can use Log10 and linear regression equation. What is the linear equation for Log10 of this data? Log10: Regression Analysis

Var.

0.988

0.994

Std. Error

0.032

Dep.

p-value

406.75

5.54E-06

log(Y)

ANOVA table Source

Regression

0.4083

Residual

0.0050

0.0010

Total

0.4100

Regression output

Confidence interval

Variables

Coefficients

Std. error

t( dt=5)

p-value

95%Upper 95%lower

Intercept

0.3623

0.1208

0.0060

0.1054

0.1361

Coefficients in terms of the modal: abx 2.303

= a, beginning value

20.168

5.54E-

1.321

= b, growth factor

32.05%

average rate of change

Predicted values for: log(Y) 95% Confidence interval

95% Prediction interval

Predicted

lower

upper

lower

upper

Leverage

1.44904

1.36616

1.53192

1.33284

1.56524

1.036

Predicted values for: Y 95% 95% Confidence Prediction interval interval

A) B) C) D) E)

Predicted

lower

upper

lower

upper

Leverage

28.12

23.24

34.03

21.52

36.75

1.036

1359) What is Log10 of the forecast for year 9?

Log10: Regression Analysis

Var.

0.988

0.994

Std. Error

0.032

Dep.

p-value

406.75

5.54E-06

log(Y)

ANOVA table Source

Regression

0.4083

Residual

0.0050

0.0010

Total

0.4100

Regression output Variables

Confidence interval Coefficients

Std. error

t( dt=5)

p-value 95%lower 95%Upper

Intercept

0.3623

0.1208

0.0060

0.1054

0.1361

Coefficients in terms of the modal: ab× 2.303

= a, beginning value

1.321

= b, growth factor

20.168

5.54E-

32.05%

average rate of change

Predicted values for: log(Y) 95% 95% Confidence Prediction interval interval t

Predicted

lower

upper

lower

upper

Leverage

1.44904

1.36616

1.53192

1.33284

1.56524

1.036

Predicted values for: Y 95% 95% Confidence Prediction interval interval

A) B) C) D) E)

Predicted

lower

upper

lower

upper

Leverage

28.12

23.24

34.03

21.52

36.75

1.036

1.449 28.122 3.337 19.325 28.12

1360) If the data appears to be increasing exponentially and we wish to forecast number of

passengers for year 9, we can use Ln and linear regression equation. What is the linear equation for Ln of this data? Date: Coded year, t

Pass(000)

3.3

4.1

4.9

6.4

9.0

12.8

16.9

Regression Analysis

Exponential r2

0.988

Adjusted r2

0.985

0.994

Std. Error

0.073

observations

Predictor variable

is the dependent variable

ANOVA table Source

Regression

2.1646

Residual

0.0266

0.0053

Total

2.1912

Regression output

Confidence interval

variables

Coefficients

std. error

t ( df=5)

p-value

406.75 5.54E-06

p-value

95% lower

95% upper

intercept

0.8342

0.278

0.0138

20.168

5.54E-06 0.2426

0.3135

Predicted values for: L 95% Confidence 95% Interval Prediction Interval t

Predicted

lower

upper

lower

upper Leverage

9 A) B) C) D) E)

3.33654

3.1457

3.52738

3.06899 3.60409

1.036

1361) What is Ln of the forecast for year 9? Data: Coded year, t

Pass(000)

3.3

4.1

4.9

6.4

9.0

12.8

16.9

Regression Analysis

Exponential r2

0.988

Adjusted r2

0.985

0.994

Std. Error

0.073

observations

Predictor variable

is the dependent variable

ANOVA table Source

Regression

2.1646

Residual

0.0266

0.0053

Total

2.1912

Regression output

Confidence interval

variables

Coefficients

intercept

0.8342

0.278

p-value

406.75 5.54E-06

std. error

t ( df=5)

p-value

95% lower

95% upper

0.0138

20.168

5.54E-06 0.2426

0.3135

Predicted values for: L 95% Confidence 95% Interval Prediction Interval t

Predicted

lower

upper

lower

upper Leverage

9 A) B) C) D) E)

1.449 28.122 3.337 19.325 1.087

3.33654

3.1457

3.52738

3.06899 3.60409

1.036

1362) What is the forecast for year 9? Data: Coded year, t

Pass(000)

3.3

4.1

4.9

6.4

9.0

12.8

16.9

Regression Analysis

Exponential r2

0.988

Adjusted r2

0.985

0.994

Std. Error

0.073

observations

Predictor variable

is the dependent variable

ANOVA table Source

Regression

2.1646

Residual

0.0266

0.0053

Total

2.1912

Regression output

Confidence interval

variables

Coefficients

intercept

0.8342

0.278

p-value

406.75 5.54E-06

std. error

t ( df=5)

p-value

95% lower

95% upper

0.0138

20.168

5.54E-06 0.2426

0.3135

Predicted values for: L 95% Confidence 95% Interval Prediction Interval t

Predicted

lower

upper

lower

upper Leverage

9 A) B) C) D) E)

3.33654

3.1457

3.52738

3.06899 3.60409

1.036

20.725 20.025 17.100 28.122 19.325

1363) If a quarterly seasonal index is 0.56, it implies that: A) the quarter's sales are 56% above the yearly average. B) the quarter's sales are 56% of the year total sales. C) the other three quarter percentages will total 44%. D) the quarter's sales are 56% of the yearly average. E) the quarter's sales are 56% below the yearly average.

1364) In the calculation of 4-quarter seasonal indices the total of the quarterly means will be: A) 4.0. B) 1.0. C) 100%. D) a variable. E) 4.0/total of the quarterly means.

1365) A plastics manufacturing performed a quarterly time series analysis for demands over the

last five years (t=0 for 1st Quarter). The analysis resulted in the following trend equation and seasonal indexes: = 920.0 + 22.6 t Quarter

Index

75.0

104.0

121.0

100.0

1365.1) Based on the seasonal indexes, which quarter is expect to have 21% more demand than

predicted by the trend line? A) 1 B) 2 C) 3 D) 4 E) 1 and 3

1365.2) Based on the seasonal indexes, which quarter is expect to have 25% less demand than

predicted by the trend line? A) 1 B) 2 C) 3 D) 4 E) 1 and 3

1365.3) Using the trend line question and the seasonal indexes, predict demand for the third

quarter of the next year. A) 1439.8 B) 519.8 C) 629.0 D) 1195.2 E) 1714.8

1365.4) If demand for period 19 was actually 1,000, what was the deseasonalized demand? A) 1045.95 B) 826.44 C) 750.00 D) 1333.33 E) 1859.47

1366) i. A typical monthly seasonal index of 107.0 indicates that sales (or whatever the variable

is) are 107 percent above the annual average. ii. Each typical seasonal index is a percent with the average for the year equal to 100. iii. The ratio-to-moving-average method eliminates the seasonal, cyclical and irregular components from the original data ( y). A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1367) i. Each typical seasonal index is a percent with the average for the year equal to 100.

ii. The ratio-to-moving-average method eliminates the seasonal, cyclical and irregular components from the original data ( y). iii. The trend component of a time series is obtained my minimizing the sum of the squares of the errors. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1368) i. The ratio-to-moving-average method eliminates the seasonal, cyclical and irregular

components from the original data ( y). ii. The cyclical component of a time series is described in terms relative to the seasonal index. iii. The irregular component of a time series is the easiest to measure. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) is a correct statement but not (ii) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1369) i. The cyclical component of a time series is described in terms relative to the seasonal

index. ii. The irregular component of a time series is the easiest to measure. iii. The ratio-to-moving average method removes the time series trend component, resulting in 12 numbers that are called specific seasonals. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1370) i. The irregular component of a time series is the easiest to measure.

ii. The ratio-to-moving average method removes the time series trend component, resulting in 12 numbers that are called specific seasonals. iii. For a quarterly time series, the initial step, using the ratio-to-moving average method, is to remove the seasonal components from the time series using a 3-month centered moving average. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are incorrect statements but (iii) is correct. C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1371) i. The ratio-to-moving average method removes the time series trend component,

resulting in 12 numbers that are called specific seasonals. ii. For a quarterly time series, the initial step, using the ratio-to-moving average method, is to remove the seasonal components from the time series using a 3-month centered moving average. iii. In the ratio-to-moving-average procedure, using the median or modified mean eliminates trend. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (ii) is a correct statement but (i) and (iii) are incorrect.

1372) i. For a quarterly time series, the initial step, using the ratio-to-moving average method, is

to remove the seasonal components from the time series using a 3-month centered moving average. ii. In the ratio-to-moving-average procedure, using the median or modified mean eliminates trend. iii. In the final step, using the ratio-to-moving-average method on quarterly data, the total of the modified means should theoretically be equal to 400 because the average of should be 100. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1373) i. In the ratio-to-moving-average procedure, using the median or modified mean

eliminates trend. ii. In the final step, using the ratio-to-moving-average method on quarterly data, the total of the modified means should theoretically be equal to 400 because the average of should be 100. iii. Seasonal variation is quite common in the retail and wholesale industries. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1374) i. In the final step, using the ratio-to-moving-average method on quarterly data, the total

of the modified means should theoretically be equal to 400 because the average of should be 100. ii. Seasonal variation is quite common in the retail and wholesale industries. iii. A typical seasonal index of 103.7 for January indicates that sales for January are below the annual average. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1375) i. In the ratio-to-moving-average procedure, using the median or modified mean

eliminates trend. ii. A typical seasonal index of 103.7 for January indicates that sales for January are below the annual average. iii. The total of the four typical quarterly indexes should equal 100.0. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1376) i. A typical monthly seasonal index of 107.0 indicates that sales (or whatever the variable

is) are 7 percent above the annual average. ii. For a quarterly time series, the initial step, using the ratio-to-moving average method, is to remove the seasonal components from the time series using a 3-month centered moving average. iii. In the final step, using the ratio-to-moving-average method on quarterly data, the total of the modified means should theoretically be equal to 400 because the average of should be 100. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1377) i. A typical monthly seasonal index of 107.0 indicates that sales (or whatever the variable

is) are 7 percent above the annual average. ii. Seasonal variation is quite common in the retail and wholesale industries. iii. A typical seasonal index of 103.7 for January indicates that sales for January are below the annual average. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1378) i. A typical monthly seasonal index of 107.0 indicates that sales (or whatever the variable

is) are 107 percent above the annual average. ii. The ratio-to-moving average method removes the time series trend component, resulting in 12 numbers that are called specific seasonals. iii. The total of the four typical quarterly indexes should equal 100.0. A) (i), (ii) and (iii) are all correct statements. B) (i) is a true statement but not (ii) and (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii) and (iii) are all false statements.

1379) i. The reason for deseasonalizing a sales series is to remove trend and cyclical

fluctuations so that we can study seasonal fluctuations. ii. Using the ratio-to-moving-average method, dividing the actual sales for a month by the typical seasonal for that month results in a figure that includes only trend, cycle and irregular fluctuations. This procedure is called deseasonalizing the sales. iii. Knowing the seasonal pattern in the form of indexes allows the retailer to deseasonalize sales. This is accomplished by dividing the actual sales for a month by the typical index for that month. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1380) i. Using the ratio-to-moving-average method, dividing the actual sales for a month by the

typical seasonal for that month results in a figure that includes only trend, cycle and irregular fluctuations. This procedure is called deseasonalizing the sales. ii. The reason for deseasonalizing a sales series is to remove trend and cyclical fluctuations so that we can study seasonal fluctuations. iii. Knowing the seasonal pattern in the form of indexes allows the retailer to deseasonalize sales. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1381) Teton Village contains shops, restaurants and motels. They have two peak seasons -

winter for skiing and summer for tourists visiting nearby parks. The specific seasonal with respect to the total sales volume for recent years are: Winter1

Spring2

Summer3

Fall4

2004

117

80.7

129.6

76.1

2005

118.6

82.5

121.4

2006

114

84.3

119.9

2007

120.7

79.6

130.7

69.6

2008

125.2

80.2

127.6

1381.1) Using the seasonal indexes below, explain the typical index for the spring season. Calculation of Seasonal Indexes 1

A) B) C) D)

1.283

0.750

1.178

0.827

1.223

0.778

1.152

0.855

1.209

0.755

1.205

0.789

1.298

0.687

1.239

0.794

mean:

1.194

0.817

1.253

0.742

4.006

adjusted:

1.192

0.815

1.251

0.741

4.000

Total sales for the spring season are typically 18.3% below the seasonal average. Total sales for the spring season are typically 18.3% above the seasonal average. Total sales for the spring season are typically 81.7% below the seasonal average. Total sales for the spring season are typically 81.5% below the seasonal average.

1381.2) Using the seasonal indexes below, explain the typical index for the fall season. Calculation of Seasonal Indexes 1

A) B) C) D)

1.283

0.750

1.178

0.827

1.223

0.778

1.152

0.855

1.209

0.755

1.205

0.789

1.298

0.687

1.239

0.794

mean:

1.194

0.817

1.253

0.742

4.006

adjusted:

1.192

0.815

1.251

0.741

4.000

Total sales for the fall season are typically 25.1% below the seasonal average. Total sales for the fall season are typically 74.2% below the seasonal average. Total sales for the fall season are typically 74.2% above the seasonal average. Total sales for the fall season are typically 31.2% seasonal average.

1382) The table below shows the sales for a plastics manufacturer recorded over the past year.

The seasonal indexes for each quarter are also provided. To track the trend for these four quarters, use the indexes to deseasonalize the sales data. Quarter

Sales

Index

738

75.0

1012

104.0

1196

121.0

962

100.0

Deseasonalized Sales

1382.1) What are deseasonalized sales for quarter 1? A) 553.5 B) 984.0 C) 1291.5 D) 184.5 E) 922.5

1382.2) What are deseasonalized sales for quarter 2? A) 973.1 B) 1052.5 C) 1291.5 D) 1012.0 E) 1027.7

1382.3) Overall, based on these four quarters, sales: A) are definitely increasing. B) are definitely decreasing. C) are constant. D) are exponentially decreasing. E) cannot be determined.

1382.4) What are deseasonalized sales for quarter 3? A) 251.2 B) 944.8 C) 988.4 D) 1147.2 E) 1196.0

1383) The Westberg Electric Company sells electric motors. The monthly trend equation, based

on four years of monthly data, is Y' = 4.4 + 0.5t. The seasonal factor for the month of March is 100. Determine the seasonally adjusted forecast for March of the fifth year. A) 29.9 B) 29.5 C) 33.0 D) 26.3

1384) The Westberg Electric Company sells electric motors. The monthly trend equation, based

on four years of monthly data, is Y' = 4.4 + 0.5t. The seasonal factor for the month of April is 98. Determine the seasonally adjusted forecast for April of the fifth year. A) 29.8 B) 29.5 C) 33.0 D) 26.3 E) 28.9

1385) The Westberg Electric Company sells electric motors. The monthly trend equation, based

on four years of monthly data, is Y' = 4.4 + 0.5t. The seasonal factor for the month of May is 85. Determine the seasonally adjusted forecast for May of the fifth year. A) 29.8 B) 29.5 C) 33.0 D) 26.3 E) 28.9

1386) The Westberg Electric Company sells electric motors. The monthly trend equation, based

on four years of monthly data, is Y' = 4.4 + 0.5t. The seasonal factor for the month of June is 105. Determine the seasonally adjusted forecast for June of the fifth year. A) 29.8 B) 29.5 C) 33.8 D) 26.3 E) 33.0

1387) For the 12 quarters between 2017 to 2019 the following data was gathered for Daily

Cottage rentals in Val des Bois, Quebec along with the corresponding summarized megastat output: Canadian$ 17Q1

!7Q2

17Q3

17Q4

18Q1 18Q2 18Q3 18Q4 19Q1 19Q2 19Q3 19Q4

350

450

550

400

375 500

575

425 365

510 520

430

Regression Equation Intercept

430

4.48 Seasonal Index

0.796

1.086

1.227

0.891

1387.1) What does the slope coefficient mean? A) The daily rental for the first quarter of 2017 was $430. B) The daily rental at for the first quarter of 2017 was $4.88. C) The daily rental is increasing by $4.48 every successive quarter. D) The daily rental is increasing by $430 every successive quarter.

1387.2) What does the y- intercept coefficient mean? A) The daily rental for the first quarter of 2017 was $430. B) The daily rental at for the first quarter of 2017 was $4.88. C) The daily rental is increasing by $4.48 every successive quarter. D) The daily rental is increasing by $430 every successive quarter.

1387.3) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 1st quarter of 2017, assuming that t=0 for the 1st quarter of 2017? A) 342.28 B) 471.85 C) 538.60 D) 395.11

1387.4) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 2nd quarter of 2017, assuming that t=0 for the 1st quarter of 2017? A) 342.28 B) 471.85 C) 538.60 D) 395.11

1387.5) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 3rd quarter of 2017, assuming that t=0 for the 1st quarter of 2017? A) 342.28 B) 471.85 C) 538.60 D) 395.11

1387.6) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 4th quarter of 2017, assuming that t=0 for the 1st quarter of 2017? A) 342.28 B) 471.85 C) 538.60 D) 395.11

1387.7) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 1st quarter of 2018, assuming that t=0 for the 1st quarter of 2017? A) 356.54 B) 491.31 C) 560.59 D) 411.07

1387.8) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 2nd quarter of 2018, assuming that t=0 for the 1st quarter of 2017? A) 356.54 B) 491.31 C) 560.59 D) 411.07

1387.9) Using both the trend information and seasonal values, what is the predicted daily rental

cost for the 3rd quarter of 2018, assuming that t=0 for the 1st quarter of 2017? A) 356.54 B) 491.31 C) 560.59 D) 411.07

1387.10)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 4th quarter of 2018, assuming that t=0 for the 1st quarter of 2017? A) 356.54 B) 491.31 C) 560.59 D) 411.07

1387.11)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 1st quarter of 2019, assuming that t=0 for the 1st quarter of 2017? A) 370.81 B) 510.77 C) 582.58 D) 427.04

1387.12)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 2nd quarter of 2019, assuming that t=0 for the 1st quarter of 2017? A) 370.81 B) 510.77 C) 582.58 D) 427.04

1387.13)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 3rd quarter of 2019, assuming that t=0 for the 1st quarter of 2017? A) 370.81 B) 510.77 C) 582.58 D) 427.04

1387.14)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 4th quarter of 2019, assuming that t=0 for the 1st quarter of 2017? A) 370.81 B) 510.77 C) 582.58 D) 427.04

1387.15)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 1st quarter of 2020, assuming that t=0 for the 1st quarter of 2017? A) 385.07 B) 530.23 C) 604.57 D) 443.01

1387.16)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 2nd quarter of 2020, assuming that t=0 for the 1st quarter of 2017? A) 385.07 B) 530.23 C) 604.57 D) 443.01

1387.17)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 3rd quarter of 2020, assuming that t=0 for the 1st quarter of 2017? A) 385.07 B) 530.23 C) 604.57 D) 443.01

1387.18)

Using both the trend information and seasonal values, what is the predicted daily rental cost for the 4th quarter of 2020, assuming that t=0 for the 1st quarter of 2017? A) 385.07 B) 530.23 C) 604.57 D) 443.01

1387.19) A) B) C) D)

1387.20) A) B) C) D)

1387.21) A) B) C) D)

What is the actual rental cost for the 1ST quarter of 2017? 375 342.28 430 350

What is the actual rental cost for the 1ST quarter of 2018? 375 350 356.54 447.92

What is the actual rental cost for the 1ST quarter of 2019? 375 370.81 365 370.81

What is the forecasted rental cost for the 1st quarter of 2021, assuming that t=0 in the 1st quarter of 2017? Take both and trend and season into consideration. A) 442.13 B) 427.87 C) 413.60 D) 399.34

1387.22)

What is the forecasted rental cost for the 2nd quarter of 2022, assuming that t=0 in the 1st quarter of 2017? Take both and trend and season into consideration. A) 442.13 B) 569.15 C) 413.60 D) 399.34

1387.23)

What is the forecasted rental cost for the 3rd quarter of 2023, assuming that t=0 in the 1st quarter of 2017? Take both and trend and season into consideration. A) 442.13 B) 670.53 C) 413.60 D) 399.34

1387.24)

What is the forecasted rental cost for the 4th quarter of 2024, assuming that t=0 in the 1st quarter of 2017? Take both and trend and season into consideration. A) 506.87 B) 427.87 C) 413.60 D) 399.34

1387.25)

1387.26)

By identifying the correct season with the highest rentals prices, what % higher on average is this season compared to the other 3 seasons? A) Q3 is 122.7 % higher than the others. B) Q3 is 22.7 % higher than the others. C) Q2 & Q3 are the same since they are both in the summer. D) There's not much difference between seasons.

1387.27)

By identifying the correct season with the lowest rental prices, what % lower on average is this season compared to the other 3 seasons? A) Q1 represents January, February and March so it has the lowest prices. B) Q1 is 79.6 % lower than the others. C) Q1 is 20.4 % lower than the others. D) Q1 & Q4 are the same since they are both in the winter.

Answer Key Test name: chapter 16 721) 722) 723) 724) 725) 726) 727) 728) 729) 730) 731) 732) 733) 734) 735) 736) 737) 738) 739) 740) 741) 742) 743) 744) 745) 746) 747) 748) 749) 750) 751) 752) 753) 754) 755) 756) 757)

C B E B D A A E B A B B A C B D C B A E E C A B B B E A C A B C C B C D B

758) D 759) D 760) B 761) A 762) E 763) E 764) E 765) Section Break 765.1) E 765.2) B 765.3) A 765.4) C 765.5) B 765.6) D 765.7) E 765.8) C 766) A 767) C 768) B 769) E 770) B 771) A 772) C 773) C 774) D 775) D 776) A 777) Section Break 777.1) C 777.2) A 777.3) E 777.4) B 778) D 779) B 780) C 781) E 782) B 783) E 784) C 785) D

786) B 787) E 788) A 789) B 790) E 791) D 792) C 793) Section Break 793.1) A 793.2) A 794) Section Break 794.1) B 794.2) A 794.3) E 794.4) C 795) A 796) A 797) D 798) E 799) Section Break 799.1) C 799.2) A 799.3) A 799.4) B 799.5) C 799.6) D 799.7) A 799.8) B 799.9) C 799.10) D 799.11) A 799.12) B 799.13) C 799.14) D 799.15) A 799.16) B 799.17) C 799.18) D 799.19) D 799.20) A

799.21) C 799.22) D 799.23) B 799.24) B 799.25) A 799.26) B 799.27) C

Student name:__________ 1388) The states of nature are: A) the choices available to the decision maker. B) the uncontrollable future events. C) a comparison of each combination of decision alternatives and the state of nature.

1389) A payoff table is needed to: A) control for possible future events. B) inform the decision maker of the choices available. C) compare each combination of decision alternative and state of nature. D) control for possible future events and inform the decision maker of the choices

available.

1390) An investor has a 35% chance of making $1000 and a 65% chance of making $10 000,

what is the expected payoff for this investor? A) $11 000 B) $6 850 C) $7 500 D) $10 000

1391) You are trying to decide in which of the three companies you should invest. Refer to the

following Payoff Table. Payoff Table Market rise

Market decline

Company A

2500

900

Company B

2300

1200

Company C

1800

1150

1391.1) If the probability of the Market rising in the next year is 0.60, which of the following

statements are correct? i. The Expected Monetary Value for Company A is $1,860. ii. The Expected Monetary Value for Company B is $1,860. iii. The Expected Monetary Value for Company C is $1,860. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

1391.2) If the probability of the Market rising in the next year is 0.60, which of the following

statements are correct? i. The Expected Monetary Value for Company A is $1,860. ii. The Expected Monetary Value for Company B is $1,860. iii. The Expected Monetary Value for Company C is $1,540. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

1391.3) If the probability of the Market rising in the next year is 0.50, which of the following

statements are correct? i. The Expected Monetary Value for Company A is $1,450. ii. The Expected Monetary Value for Company B is $1,600. iii. The Expected Monetary Value for Company C is $1,475. A) (i), (ii) and (iii) are all correct statements. B) (iii) is a correct statement but not (ii) or (ii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

1391.4) If the probability of the Market rising in the next year is 0.60, which of the following

statements are correct? i. The Opportunity Loss for Company A is $1,860. ii. The Opportunity Loss for Company B is $1,860. iii. The Opportunity Loss for Company C is $1,540. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

1391.5) If the market rises in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $200. ii. The Opportunity Loss for Company B is $200. iii. The Opportunity Loss for Company C is $200. A) (i), (ii) and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii) and (iii) are all false statements.

1391.6) If the market rises in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $200. ii. The Opportunity Loss for Company B is $200. ii. The Opportunity Loss for Company C is $700. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1391.7) If the market declines in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $300. ii. The Opportunity Loss for Company B is $0. iii. The Opportunity Loss for Company C is $50. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1391.8) If the market declines in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $300. ii. The Opportunity Loss for Company B is $30. iii. The Opportunity Loss for Company C is $500. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1391.9) If the probability of the market declining in the next year is 0.4, which of the following

statements are correct? i. The Expected Opportunity Loss for Company A is $300. ii. The Expected Opportunity Loss for Company B is $30. iii. The Expected Opportunity Loss for Company C is $500. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1391.10)

If the probability of the market declining in the next year is 0.4, which of the following statements are correct? i. The Expected Opportunity Loss for Company A is $120. ii. The Expected Opportunity Loss for Company B is $120. iii. The Expected Opportunity Loss for Company C is $440. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1391.11)

If the probability of the market declining in the next year is 0.4, which of the following statements are correct? i. The Expected Opportunity Loss for Company A is $20. ii. The Expected Opportunity Loss for Company B is $120. iii. The Expected Opportunity Loss for Company C is $440. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1391.12)

If the probability of the market declining in the next year is 0.4, which of the following statements are correct? i. The Expected value of stock purchased under conditions of certainty is $1,980. ii. The Expected value of stock purchased under conditions of certainty is $120. iii. The Expected value of stock purchased under conditions of certainty is $440. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (iii) is a correct statement but not (i) or (ii). E) (i), (ii), and (iii) are all false statements.

1391.13)

If the probability of the market declining in the next year is 0.4, which of the following statements are correct? i. The Expected value of stock purchased under conditions of certainty is $1,980. ii. The Expected value of perfect information is $120. iii. The Expected value of perfect information is $180. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (iii) is a correct statement but not (i) or (ii). E) (i) and (ii) are correct statements but not (iii).

1392) You are trying to decide in which of the three companies you should invest. Refer to the

following Payoff Table. Payoff Table Market rise

Market decline

Company A

2000

900

Company B

2200

1000

Company C

1800

1150

1392.1) If the probability of the Market rising in the next year is 0.50, which of the following

statements are correct? i. The Expected Monetary Value for Company A is $1,450. ii. The Expected Monetary Value for Company B is $1,960. iii. The Expected Monetary Value for Company C is $1,500. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

1392.2) If the probability of the Market rising in the next year is 0.50, which of the following

statements are correct? i. The Opportunity Loss for Company A is $1,460. ii. The Opportunity Loss for Company B is $1,600. iii. The Opportunity Loss for Company C is $1,475. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

1392.3) If the market rises in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $200. ii. The Opportunity Loss for Company B is $0. iii. The Opportunity Loss for Company C is $400. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (i) and (ii) are correct statements but not (iii). E) (i), (ii), and (iii) are all false statements.

1392.4) If the market rises in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $200. ii. The Opportunity Loss for Company B is $200. iii. The Opportunity Loss for Company C is $700. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1392.5) If the market declines in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $250. ii. The Opportunity Loss for Company B is $150. iii. The Opportunity Loss for Company C is $0. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1392.6) If the market declines in the next year, which of the following statements are correct?

i. The Opportunity Loss for Company A is $250. ii. The Opportunity Loss for Company B is $30. iii. The Opportunity Loss for Company C is $500. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1392.7) If the probability of the market declining in the next year is 0.5, which of the following

statements are correct? i. The Expected Opportunity Loss for Company A is $225. ii. The Expected Opportunity Loss for Company B is $75. iii. The Expected Opportunity Loss for Company C is $200. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1392.8) If the probability of the market declining in the next year is 0.5, which of the following

statements are correct? i. The Expected Opportunity Loss for Company A is $120. ii. The Expected Opportunity Loss for Company B is $75. iii. The Expected Opportunity Loss for Company C is $200. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1392.9) If the probability of the market declining in the next year is 0.5, which of the following

statements are correct? i. The Expected Opportunity Loss for Company A is $20. ii. The Expected Opportunity Loss for Company B is $75. iii. The Expected Opportunity Loss for Company C is $440. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1392.10)

If the probability of the market declining in the next year is 0.5, which of the following statements are correct? i. The Expected value of stock purchased under conditions of certainty is $1,675. ii. The Expected value of stock purchased under conditions of certainty is $2,200. iii. The Expected value of stock purchased under conditions of certainty is $1,150. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (iii) is a correct statement but not (i) or (ii). E) (i), (ii), and (iii) are all false statements.

1392.11)

If the probability of the market declining in the next year is 0.5, which of the following statements are correct? i. The Expected value of stock purchased under conditions of certainty is $1,980. ii. The Expected value of perfect information is $75. iii. The Expected value of perfect information is $180. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (iii) is a correct statement but not (i) or (ii). E) (i) and (ii) are correct statements but not (iii).

1392.12)

If the probability of the market declining in the next year is 0.5, which of the following statements are correct? i. The Expected value of stock purchased under conditions of certainty is $1,675. ii. The Expected value of perfect information is $75. iii. The Expected value of perfect information is $180. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (ii) is a correct statement but not (i) or (iii). D) (iii) is a correct statement but not (i) or (ii). E) (i) and (ii) are correct statements but not (iii).

1393) Consider the following decision table in which w, x, y and z are decision alternatives and

A & B are the two possible states of nature with probabilities 0.40 and 0.60. A(0.4)

B(0.6)

-50

100

-200

500

150

1393.1) The expected value for decision W is: A) 40 B) 75 C) 80 D) 220 E) 30

1393.2) The expected value for decision X is: A) 40 B) 75 C) 80 D) 220 E) 30

1393.3) The expected value for decision Y is: A) 40 B) 28 C) 50 D) 22 E) 15

1393.4) The expected value for decision Z is: A) 110 B) 200 C) 170 D) 140 E) 150

1394) Below is the payoff table for two stocks based on whether the market rises or declines.

Which of the following represents the opportunity loss table? Stock

Market Rise

Market Decline

Stock A

2,000

1,500

Stock B

2,500

1,000

Stock

Market Rise

Market Decline

Stock A

500

Stock B

500

Stock

Market Rise

Market Decline

Stock A

500

Stock B

Stock

Market Rise

Market Decline

Stock A

500

Stock B

500

1395) Suppose that the below represents the opportunity loss table for three stocks based on

whether the market rises or declines. If there is a 30% chance of the market rising and a 70% chance of it declining, what is the expected opportunity loss for stock C? Stock

Market Rise

Market Decline

Stock A

700

Stock B

800

Stock C

500

1000

A) B) C) D) E)

490 850 240 910 370

1396) Given the following decision table in which x, y and z are decision alternatives and A &

B are states of nature. x

-50

-200

+10

+150

+450

+40

1396.1) Which alternative would be chosen if using the maximax criterion? A) A B) B C) x D) y E) z

1396.2) Which alternative would be chosen if using the maximin criterion? A) A B) B C) x D) y E) z

1397) The maximin strategy: A) minimizes the maximum gain. B) maximizes the minimum gain. C) minimizes the maximum regret. D) maximizes the minimum regret.

1398) i. EVPI = Expected value under conditions of certainty-Optimal decision under

conditions of uncertainty. ii. Three regret strategies that are often used are Maximin, Maximax, and Minimax. iii. Rankings of the decision alternatives are frequently not highly sensitive to changes in the applied probabilities within a plausible range. A) (i), (ii), and (iii) are all correct statements. B) (i) is a correct statement but not (ii) or (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

1399) The alternative which offers the lowest EOL is the same as the one which: A) offers the highest EMV. B) maximizes the minimum gain. C) minimizes the maximum loss. D) maximizes the maximum gain.

1400) For the below payoff table, if P(S1) = 0.3, P(S2) = 0.5 and P(S3) = 0.2, what decision

would you recommend? State of Nature Alternative

$100

$50

$40

200

100

A) Go with Alternative A. It has an expected payoff of $63. B) Go with Alternative B. It has an expected payoff of $72. C) Go with Alternative C. It has an expected payoff of $63.

1401) A decision tree: A) uses a box to indicate the point at which a decision must be made. B) is a picture of all the possible courses of action and the consequent possible

outcomes. C) contains branches going out from the box which indicate the alternatives under consideration. D) is a picture of all the possible courses of action and the consequent possible outcomes, uses a box to indicate the point at which a decision must be made and contains branches going out from the box which indicate the alternatives under consideration.

1402) Determine the expected opportunity loss for the following payoff table.

A) B) C) D)

Event

Payoff($)

Probability of Event

Market rise

$500

0.4

Market decline

0.6

$0 $200 $300 $500

1403) Determine the expected value for the following payoff table.

A) B) C) D)

Event

Payoff($)

Probability of Event

Market rise

$500

0.4

Market decline

$350

0.6

$0 $200 $300 $410

1404) Determine the expected profit for the following distribution.

A) B) C) D)

$0 $20 $30 $41

p(X)

0.1

0.2

0.7

1405) Given the payoff table below, determine the profit and size of warehouse that would be

built, using the maximin criterion. States of Nature

A) B) C) D)

Alternatives

Low Demand

High Demand

Small warehouse

$8 million

Medium warehouse

$5 million

$15 million

Large warehouse

$11 million

$22 million

$8 million, small warehouse $5 million, medium warehouse $11 million, large warehouse $15 million, medium warehouse

1406) Given the payoff table below, determine the profit and size of warehouse that would be

built, using the maximax criterion. States of Nature

A) B) C) D) E)

Alternatives

Low Demand

High Demand

Small warehouse

$8 million

Medium warehouse

$5 million

$15 million

Large warehouse

$11 million

$22 million

$8 million, small warehouse $5 million, medium warehouse $11 million, large warehouse $15 million, medium warehouse $22 million, large warehouse

1407) Given the payoff table below, determine the expected value and size of warehouse that

would be built, given a probability of 0.7 and 0.3 to the low and high demands, respectively. States of Nature

A) B) C) D) E)

Alternatives

Low Demand

High Demand

Small warehouse

$8 million

Medium warehouse

$5 million

$15 million

Large warehouse

$11 million

$22 million

$8 million, small warehouse $5 million, medium warehouse $14.3 million, large warehouse $12 million, medium warehouse $22 million, large warehouse

1408) You have a decision to invest $10,000 in any of four different companies. You estimate

the probabilities that the economy will be favourable or unfavourable and you estimate the percent returns over the next year. State of Nature Company

Favorable (p=0.4)

Unfavorable (p=0.6)

11%

10%

-2%

1408.1) Based on expected opportunity loss, which company do you choose? A) Company 1 B) Company 2 C) Company 3 D) Company 4

1408.2) Based on the maximin criterion, what is the choice? A) Company 1 B) Company 2 C) Company 3 D) Company 4

1408.3) Based on expected value, what company do you choose? A) Company 1 B) Company 2 C) Company 3 D) Company 4

1408.4) What is the expected value for Company 3? A) 0% B) 3% C) -2% D) 1.2%

1408.5) What is the expected value for Company 2? A) 9.20% B) 9% C) 9.6% D) 9.4%

1408.6) What is the expected value for Company 1? A) 9.20% B) 9% C) 9.6% D) 9.4%

1408.7) What is the expected value for Company 4? A) 5.20% B) 5.4% C) 5.6% D) 9.4%

1408.8) Which company is chosen using the maximax criterion? A) Company 1 B) Company 2 C) Company 3 D) Company 4

1409) You are making plans for summer employment. You have 3 different job prospects as a

server. The local golf course, the casino or on a center town patio. You understand that the weather will have an impact on the amount of tips you will earn. Long term weather forecasts predict a S1 = 50% chance of a sunny and warm summer, S2 = 30% chance of a rainy and cold summer and a S3 = 20% chance of a sunny and cold summer. Given the following payoff table: States of Nature JOB

S1=50%

S2=30%

S3=20%

Golf course

$15000

$10000

$5000

Casino

$8000

$9000

$13000

Patio

$18000

$8000

$4000

1409.1) Using the expected monetary value criterion what is the expected value of working at the

Golf course? A) 15000 B) 14600 C) 11500 D) 9300 E) 12200

1409.2) Using the expected monetary value criterion what is the expected value of working at the

Casino? A) 13000 B) 14600 C) 11500 D) 9300 E) 12200

1409.3) Using the expected monetary value criterion what is the expected value of working at the

Patio? A) B) C) D) E)

18000 14600 11500 9300 12200

1409.4) Using the expected opportunity loss criterion what is the expected opportunity loss of

working at the Golf course? A) 0 B) 2400 C) 3000 D) 3100 E) 5300

1409.5) Using the expected opportunity loss criterion what is the expected opportunity loss of

working at the Casino? A) 10000 B) 2400 C) 3000 D) 3100 E) 5300

1409.6) Using the expected opportunity loss criterion what is the expected opportunity loss of

working at the Patio? A) 0 B) 2400 C) 3000 D) 3100 E) 5300

1409.7) Using the expected opportunity loss criterion which job would you choose? A) Golf course B) Casino C) Patio D) Either Golf course or Patio as they're equal. E) Either Golf course or Casino as they're the same.

1409.8) Using the expected monetary value criterion which job would you choose? A) Golf course B) Casino C) Patio D) Either Golf course or Patio as they're equal. E) Either Golf course or Casino as they're the same.

1409.9) Calculate the amount of money you would make if you had perfect information.

conditions under certainty. A) 18000 B) 14600 C) 12200 D) 2400

1409.10) A) B) C) D)

What is the expected value of Perfect Information? 18000 14600 12200 2400

1410) You are making plans for summer employment. You have 3 different job prospects as a

server. The local golf course, the casino or on a center town patio. You understand that the weather will have an impact on the amount of tips you will earn. Long term weather forecasts predict a S1 = 20% chance of a sunny and warm summer, S2 = 30% chance of a rainy and cold summer and a S3 = 50% chance of a sunny and cold summer. Given the following payoff table: States of Nature JOB

S1=20%

S2=30%

S3=50%

Golf course

$15000

$10000

$5000

Casino

$8000

$9000

$13000

Patio

$18000

$8000

$4000

1410.1) Using the expected monetary value criterion what is the expected value of working at the

Golf course? A) 15000 B) 10800 C) 8500 D) 8000 E) 5000

1410.2) Using the expected monetary value criterion what is the expected value of working at the

Casino? A) 9000 B) 10800 C) 8500 D) 8000 E) 13000

1410.3) Using the expected monetary value criterion what is the expected value of working at the

Patio? A) B) C) D) E)

18000 10800 8500 8000 4000

1410.4) Using the expected opportunity loss criterion what is the expected opportunity loss of

working at the Golf course? A) 5100 B) 4600 C) 2300 D) 5000 E) 4000

1410.5) Using the expected opportunity loss criterion what is the expected opportunity loss of

working at the Casino? A) 5100 B) 4600 C) 2300 D) 5000 E) 4000

1410.6) Using the expected opportunity loss criterion what is the expected opportunity loss of

working at the Patio? A) 5100 B) 4600 C) 2300 D) 5000 E) 4000

1410.7) Using the expected opportunity loss criterion which job would you choose? A) Golf course B) Casino C) Patio D) Either Golf course or Patio as they're equal. E) Either Golf course or Casino as they're the same.

1410.8) Using the expected monetary value criterion which job would you choose? A) Golf course B) Casino C) Patio D) Either Golf course or Patio as they're equal. E) Either Golf course or Casino as they're the same.

1410.9) Calculate the amount of money you would make if you had Perfect information.

Conditions under certainty. A) 2300 B) 10800 C) 13100 D) 18000 E) 15000

1410.10) A) B) C) D)

Under the Maximin criterion which job would you take? Golf course Casino Patio Patio and Casino

1410.11) A) B) C) D)

Under the Maximax criterion which job would you take? Golf course Casino Patio Patio and Casino

Answer Key Test name: chapter 17 800) B 801) C 802) B 803) Section Break 803.1) D 803.2) A 803.3) A 803.4) E 803.5) C 803.6) D 803.7) A 803.8) B 803.9) E 803.10) A 803.11) D 803.12) B 803.13) E 804) Section Break 804.1) B 804.2) E 804.3) A 804.4) B 804.5) A 804.6) B 804.7) A 804.8) D 804.9) C 804.10) B 804.11) C 804.12) E 805) Section Break 805.1) A 805.2) D 805.3) B 805.4) A 806) C 807) B

808) Section Break 808.1) D 808.2) E 809) B 810) A 811) A 812) B 813) D 814) B 815) D 816) B 817) C 818) E 819) C 820) Section Break 820.1) B 820.2) B 820.3) B 820.4) A 820.5) C 820.6) A 820.7) C 820.8) A 821) Section Break 821.1) C 821.2) D 821.3) E 821.4) D 821.5) E 821.6) B 821.7) C 821.8) C 821.9) B 821.10) D 822) Section Break 822.1) C 822.2) B 822.3) D 822.4) B 822.5) C

822.6) A 822.7) B 822.8) B 822.9) C 822.10) B 822.11) C