Applied Statistics in Business and Economics 7th Edition by David Doane & Lori Seward TEST BANK. by ACADEMIAMILL

Chapter 1 1) "Bob must be rich. He’s a lawyer, and lawyers make lots of money." This statement best illustrates which fallacy?

A) using poor survey methods B) confusing significance with importance C) unconscious bias D) generalizing from an average to an individual

Which is not an ethical obligation of a statistician?

A) to know and follow accepted procedures B) to ensure data integrity and accurate calculations C) to support client wishes in drawing conclusions from the data D) to acknowledge sources of financial support

Which of the following statements is correct?

A) A parameter is a measure that is calculated from a sample. B) Statistics is the science of collecting, organizing, analyzing, interpreting, and presenting data. C) For day-to-day business data analysis, most firms rely on a large staff of expert statisticians. D) A statistical test result that is significant also has practical importance.

Which is least likely to be an application where statistics will be useful? A) predicting whether an airfare is likely to rise or fall B) designing the most desirable features for a ski pass C) deciding whether offering Rice Krispies improves restaurant sales D) choosing the wording of a corporate policy prohibiting smoking

5) Because 25 percent of the students in my morning statistics class watch eight or more hours of television a week, I conclude that 25 percent of all students at the university watch eight or more hours of television a week. The most important logical weakness of this conclusion would be Version 1 1

A) relying on a sample instead of surveying every student. B) using a sample that may not be representative of all students. C) failing to correct for unconscious interviewer bias. D) assuming cause and effect where none exists.

Which of the following is not a characteristic of an ideal statistician?

A) technically current (e.g., software) B) communicates well (both written and oral) C) always agrees with client’s conclusions D) can deal with imperfect information

Which of the following statements is not true?

A) Statistics helps refine theories through ongoing hypothesis testing. B) Statistics is the science of collecting, organizing, analyzing, interpreting, and presenting data. C) Estimating parameters is an important aspect of descriptive statistics. D) Statistical challenges include imperfect data and practical constraints.

Version 1

Which is not a practical constraint facing the business researcher or data analyst?

A) Time and money are always limited. B) The world is no laboratory, so some experiments are impractical. C) Research on human subjects is fraught with danger and ethical issues. D) Survey respondents usually will tell the truth if well compensated.

Which is not an essential characteristic of a good business data analyst?

A) is an effective writer B) stays current on techniques C) has a Ph.D. or Master’s degree in statistics D) can deal with imperfect information

10)

An ethical statistical consultant would not always

A) follow accepted statistical procedures. B) support management’s desired conclusions. C) acknowledge sources of financial support. D) report limitations of the data.

11)

GM's experience with faulty ignition switches suggests that

A) statistics is not applicable to automotive manufacturing. B) limited data may still contain important clues. C) good engineers can eliminate all risks. D) ignition switches are inherently dangerous.

Version 1

12)

Which is not a goal of the ethical data analyst?

A) to be an honest broker of data B) to learn to downplay inconvenient data C) to understand the firm’s code of ethics (or help create one) D) to look for hidden agendas in data collection

13)

Which of the following statements is not true?

A) A statistic is a single measure (usually numerical) that is calculated from a sample. B) Statistics is the science of collecting, organizing, analyzing, interpreting, and presenting data. C) For day-to-day business data analysis, most firms rely on a large staff of expert statisticians. D) A statistical test may be significant yet have no practical importance.

14) "Smoking is not harmful. My Aunt Harriet smoked, but lived to age 90." This best illustrates which fallacy is not illustrated, A) Unconscious bias. B) Post hoc reasoning. C) Small sample generalization.

15) Which best illustrates the distinction between statistical significance and practical importance?

Version 1

A) "This year, 360 of 440 statistics students at Oxnard Technical College rented their textbooks, compared with 110 of 330 students last year. This is a significant increase." B) "Our new manufacturing technique has increased the life of the 80 GB USB AsimoDrive external hard disk significantly, from 240,000 hours to 250,000 hours." C) "In 50,000 births, the new vaccine reduced the incidence of infant mortality in Morrovia significantly from 14.2 deaths per 1000 births to 10.3 deaths per 1000 births." D) "The new Sky Penetrator IV business jet’s cruising range has increased significantly from 3,975 miles to 4,000 miles."

16) "Circulation fell in the month after the new editor took over the newspaper Oxnard News Herald. The new editor should be fired." Which is not a serious fallacy in this conclusion?

A) generalizing from a small sample B) applying post hoc reasoning C) failing to identify causes D) using a biased sample

17)

An ethical data analyst would be least likely to

A) check data for accuracy. B) cite his/her data sources and their limitations. C) acknowledge sources of financial support. D) rely on consultants for all calculations.

18)

"Tom’s SUV rolled over. SUVs are dangerous." This best illustrates which fallacy?

Version 1

A) unconconcious bias B) significance versus practical importance C) post hoc reasoning D) small sample generalization

19) "Bob didn’t wear his lucky T-shirt to class, so he failed his chemistry exam." This best illustrates which fallacy?

A) pitfall 7 B) poor survey methods C) post hoc reasoning D) more than one of the above

20)

Which is not a reason for an average student to study statistics?

A) improve technical writing skills B) gain information management skills C) enhance technical literacy D) learn investment strategies

21)

Which is least likely to involve the application of statistics in business?

A) auditing supplier invoices for correct payment B) writing strategic decisions C) looking for patterns in a large marketing database D) making forecasts of several key product lines

Version 1

22)

Which is not a likely task of descriptive statistics?

A) summarizing a sample B) describing data numerically C) estimating unknown parameters D) making visual displays of data

23)

We would associate the term inferential statistics with which task?

A) making visual displays of data B) estimating unknown parameters C) describing a sample of data D) tabulating a survey

24)

A good data analyst

A) removes data if so instructed by client. B) works alone to avoid team conflicts. C) communicates with numbers rather than with graphs. D) reports findings that may contradict client’s ideas.

25)

Which is not an analytical method commonly used to improve business decisions?

A) descriptive analytics B) predictive analytics C) prescriptive analytics D) reactive analytics

Version 1

26)

Choosing actions that will result in the best outcome for the company and its customers is

A) descriptive analytics. B) predictive analytics. C) prescriptive analytics. D) reactive analytics.

27)

Which issue isleast likely arise in machine learning (ML) and artificial intelligence (AI)?

A) identifying ethical biases in training data B) improving natural language processing C) too many skilled programmers with business skills D) massive warehouses of real-time information

28)

Which of the following statements isnot correct?

A) A parameter is a measure that is calculated from a population. B) Statistics is the science of collecting, organizing, analyzing, interpreting, and presenting data. C) Most firms rely on employees who have basic statistical knowledge to perform day-today statistical analysis rather than hiring a statistical consultant. D) A statistical test result that is significant also has practical importance.

29)

Which of the following statements isnot correct?

Version 1

A) Summarizing performance measures from large data sets is an example of predictive analytics. B) Formulating a plan of action based on large data sets and algorithmic outputs is an example of prescriptive analytics. C) Calculating click-through rate for your online customers viewing your webpage is an example of descriptive analytics. D) Setting the optimal pricing scheme to maximize revenue for a hotel is an example of prescriptive analytics.

30)

Using data to develop models that forecast customer behavior would be

A) descriptive analytics. B) predictive analytics. C) prescriptive analytics. D) reactive analytics.

31) data.

Statistics is the science of collecting, organizing, analyzing, interpreting, and presenting

⊚ ⊚

true false

32) Inferential statistics refers to generalizing from a sample to a population, estimating unknown population parameters, drawing conclusions, and making decisions. ⊚ true ⊚ false

33) Descriptive statistics refers to summarizing data rather than generalizing about the population.

Version 1

⊚ ⊚

true false

34) Estimating parameters and testing hypotheses are important aspects of descriptive statistics. ⊚ ⊚

true false

35) Testing all incoming emergency patients for COVID-19 will yield a valid estimate of the disease prevalence in the general population. ⊚ ⊚

36)

true false

Empirical data are collected through observations and experiments. ⊚ ⊚

true false

37) Business intelligence refers to collecting, storing, accessing, and analyzing data on the company’s operations in order to make better business decisions. ⊚ ⊚

true false

38) When a statistician omits data contrary to her findings in a study, she is justified as long as the sample supports her objective. ⊚ ⊚

Version 1

true false

39)

A strong correlation between A and B would imply that B is caused by A. ⊚ ⊚

true false

40) When one concludes that becauseB followsA thenB is caused byA, they are falling subject to thepost hoc fallacy. ⊚ ⊚

41)

A statistical test may be significant yet have no practical importance. ⊚ ⊚

42)

true false

Valid statistical inferences cannot be made when sample sizes are small. ⊚ ⊚

true false

43) Statistics is an essential part of critical thinking because it allows us to transform the empirical evidence from a sample so it will agree with our preferred conclusions. ⊚ ⊚

44)

true false

Statistical challenges include imperfect data, practical constraints, and ethical dilemmas.

Version 1

⊚ ⊚

45)

A business data analyst needs a Ph.D. in statistics. ⊚ ⊚

46)

true false

The science of statistics tells us whether the sample evidence is convincing. ⊚ ⊚

true false

47) Pitfalls to consider in a statistical test include nonrandom samples, small sample size, and lack of causal links. ⊚ ⊚

true false

48) In business communication, a table of numbers is preferred to a graph because it is more able to convey meaning. ⊚ true ⊚ false

49)

Statistical data analysis can often distinguish between realversus perceived ethical issues. ⊚ ⊚

Version 1

true false

50) Excel has limited use in business because advanced statistical software is widely available. ⊚ ⊚

51)

Statistics helps surmount language barriers to solve problems in multinational businesses. ⊚ ⊚

52)

true false

Statistics can help you handle either too little or too much information. ⊚ ⊚

true false

53) Predicting a presidential candidate’s percentage of the statewide vote from a sample of 800 voters would be an example of inferential statistics. ⊚ ⊚

true false

54) Surveying electric vehicle owners would provide a representative random sample of Americans’ views on global warming policies. ⊚ ⊚

true false

55) An example of descriptive statistics would be reporting the percentage of students in your accounting class that attended the review session for the last exam.

Version 1

⊚ ⊚

true false

56) The Bureau of Labor Statistics has forecasted a drop in the number of jobs requiring statistical knowledge for the next decade. ⊚ ⊚

57)

true false

Analytics can only be used to look backwards at business performance. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 01_7e_Doane 1) D 2) C 3) B 4) D 5) B 6) C 7) C 8) D 9) C 10) B 11) B 12) B 13) C 14) C 15) B 16) D 17) D 18) D 19) C 20) D 21) B 22) C 23) B 24) D 25) D 26) C Version 1

27) C 28) D 29) A 30) B 31) TRUE 32) TRUE 33) TRUE 34) FALSE 35) FALSE 36) TRUE 37) TRUE 38) FALSE 39) FALSE 40) TRUE 41) TRUE 42) FALSE 43) FALSE 44) TRUE 45) FALSE 46) TRUE 47) TRUE 48) FALSE 49) TRUE 50) FALSE 51) TRUE 52) TRUE 53) TRUE 54) FALSE 55) TRUE 56) FALSE Version 1

57) FALSE

Version 1

CHAPTER 2 1) An investment firm rates bonds for Aard Company Incorporated as "B+," while bonds of Deva Corporated are rated "AA." Which level of measurement would be appropriate for such data? A) nominal B) ordinal C) interval D) ratio

Which variable is least likely to be regarded as ratio data?

A) length of time required for a randomly chosen vehicle to cross a toll bridge (minutes) B) weight of a randomly chosen student (pounds) C) number of fatalities in a randomly chosen traffic disaster (persons) D) student’s evaluation of a professor’s teaching (Likert scale)

Which type of data could be used to calculate an average?

A) nominal B) ordinal C) interval D) none of these responses

Which of the following is numerical data?

Version 1

A) your gender B) the brand of cell phone you own C) whether you have an American Express card D) the fuel economy (MPG) of your car

Measurements from a sample are called

A) statistics. B) inferences. C) parameters. D) variables.

Measurements summarizing a population are called

A) statistics. B) inferences. C) parameters. D) variables.

Quantitative variables use which two levels of measurement? A) ordinal and ratio B) interval and ordinal C) nominal and ordinal D) interval and ratio

Temperature in degrees Fahrenheit is an example of a(n)

Version 1

variable.

A) nominal B) ordinal C) interval D) ratio

Using a sample to make generalizations about an aspect of a population is called

A) data mining. B) descriptive statistics. C) random sampling. D) statistical inference.

10)

Your telephone area code is an example of a(n)

variable.

A) nominal B) ordinal C) interval D) ratio

11)

Which is least likely to be regarded as a ratio variable? A) a critic’s rating of a restaurant on a 1 to 4 scale B) automobile exhaust emission of nitrogen dioxide (milligrams per mile) C) number of customer complaints per day at a cable TV company office D) cost of an eBay purchase

12)

Automobile exhaust emission of CO2 (milligrams per mile) is

Version 1

data.

A) nominal B) ordinal C) interval D) ratio

13) Your rating of the food served at a local restaurant using a three-point scale of 0 = gross, 1 = decent, 2 = yummy is data.

A) nominal B) ordinal C) interval D) ratio

14)

The number of passengers "bumped" on a particular airline flight is

data.

A) nominal B) ordinal C) interval D) ratio

15)

Which should not be regarded as a continuous random variable?

A) tonnage carried by a randomly chosen oil tanker at sea B) wind velocity at 7 o’clock this morning C) number of personal fouls by the Miami Heat in a game D) length of time to play a Wimbledon tennis match

Version 1

16)

Which of the following is not true?

A) Categorical data have values that are described by words rather than numbers. B) Categorical data are also referred to as nominal or qualitative data. C) The number of checks processed at a bank in a day is categorical data. D) Numerical data can be either discrete or continuous.

17)

Which of the following is true?

A) The type of charge card used by a customer (Visa, MasterCard, AmEx) is ordinal data. B) The duration (minutes) of a flight from Boston to Minneapolis is ratio data. C) The number of Nobel Prize–winning faculty at Oxnard University is continuous data. D) The number of regional warehouses owned by Jankord Industries is ordinal data.

18)

Which statement is correct?

A) Judgment sampling is preferred to systematic sampling. B) Sampling without replacement introduces bias in our estimates of parameters. C) Cluster sampling is useful when strata characteristics are unknown. D) Focus groups usually work best without a moderator.

19)

A Likert scale

A) yields interval data if scale distances are equal. B) must have an even number of scale points. C) must have a verbal label on each scale point. D) is rarely used in marketing surveys.

Version 1

20)

Which is most nearly correct regarding sampling error?

A) It can be eliminated by increasing the sample size. B) It cannot be eliminated by any statistical sampling method. C) It can be eliminated by using Excel’s =RANDBETWEEN() function. D) It can be eliminated by utilizing systematic random sampling.

21)

The necessary sample size doesnot depend on

A) the type of sampling method used. B) the inherent variability in the population. C) the desired precision of the estimate. D) the purpose of the study.

22)

Which statement is false?

A) Random dialing phone surveys have low response and are poorly targeted. B) Selection bias means that many respondents dislike the interviewer. C) Simple random sampling requires a list of the population. D) Web surveys are economical but suffer from nonresponse bias.

23)

Judgment sampling is sometimes preferred over random sampling, for example, when

A) the desired sample size is much larger than the population. B) the sampling budget is large and the population is conveniently located. C) time is short and the sampling budget is limited. D) the population is readily accessible and sampling is nondestructive.

Version 1

24)

An advantage of convenience samples is that

A) the required sample size is easier to calculate. B) sampling error can be reduced. C) computation of statistics is easier. D) they are often quicker and cheaper.

25) On randomly-chosen days and times of day, the Federal Aviation Administration records the peak noise from departing private business jets as measured by a ground-level observer at a point one mile from the end of the departure runway. The jet size (light, midsize, super-midsize, large) is noted. Average noise level is then calculated by aircraft size. This most nearly resembles which type of sample?

A) biased sample B) simple random sample C) judgment sample D) stratified sample

26) Professor Hardtack chose a sample of 7 students from his statistics class of 35 students by picking every student who was wearing red that day. Which kind of sample is this?

A) simple random sample B) judgment sample C) systematic sample D) convenience sample

27) Thirty work orders are selected from a filing cabinet containing 500 work order folders by choosing every 15th folder. Which sampling method is this?

Version 1

A) simple random sample B) systematic sample C) stratified sample D) cluster sample

28)

Which of the following is not a likely reason for sampling?

A) the destructive nature of certain tests B) the physical impossibility of checking all the items in the population C) prohibitive cost of studying the entire population D) the expense of obtaining tables of random numbers

29)

Comparing a census of a large population to a sample drawn from it, we expect that the

A) sample is usually a more practical method of obtaining the desired information. B) accuracy of the observations in the census is surely higher than in the sample. C) sample must be a large fraction of the population to be accurate.

30)

A stratified sample is sometimes recommended when

A) the sample size is very large. B) the population is small compared to the sample. C) distinguishable strata can be identified in the populations. D) the population is spread out geographically.

31)

A random sample is one in which the

Version 1

A) probability that an item is selected for the sample is the same for all population items. B) population items are selected haphazardly by experienced workers. C) items to be selected from the population are specified based on expert judgment. D) probability of selecting a population item depends on the item’s data value.

32)

An advantage of convenience samples over random samples is that

A) they are easy to analyze. B) it is easier to determine the sample size needed. C) it is easier to calculate the sampling errors involved. D) data collection cost is reduced.

33) To measure satisfaction with its cell phone service, AT&T takes a stratified sample of its customers by age and location. Which is an advantage of this type of sampling, as opposed to other sampling methods?

A) It is less intrusive on customers’ privacy. B) It does not require random numbers. C) It gives faster results. D) It can give more accurate results.

34) A marketing professor wants to know how many MBA students would take a summer elective in international accounting and gives a survey to a marketing class she was teaching. Which kind of sample is this?

A) simple random sample B) cluster sample C) systematic sample D) convenience sample

Version 1

35)

A binary variable (also called a dichotomous variable or dummy variable) has

A) only two possible values. B) continuous scale values. C) rounded data values. D) ordinal or interval values.

36) A population has groups that have a small amount of variation within them, but large variation among or between the groups themselves. The proper sampling technique is

A) simple random. B) stratified. C) cluster. D) judgment.

37) A manager choses two people from a team of eight to give an oral presentation because she felt they were representative of the whole team’s views. What sampling technique did she use in choosing these two people?

A) convenience B) simple random C) judgment D) cluster

38) A marketing survey was sent to random samples of households in ten different neighborhoods near a new shopping mall. This is an example of

Version 1

A) convenience sampling B) simple random sampling C) judgment sampling D) cluster sampling

39)

Sampling bias can best be reduced by

A) using convenience sampling. B) having a computer tabulate the results. C) utilizing random sampling. D) taking a judgment sample.

40)

A sampling technique used when groups are defined by their geographical location is

A) cluster sampling. B) convenience sampling. C) judgment sampling. D) random sampling.

41) If we choose 500 random numbers using Excel’s function =RANDBETWEEN(1,99), we would most likely find that

A) numbers near the mean (50) would tend to occur more frequently. B) numbers near 1 and 99 would tend to occur less frequently. C) some numbers would occur more than once. D) the numbers would have a clear pattern.

Version 1

42)

A problem with nonrandom sampling is that

A) larger samples need to be taken to reduce the sampling error inherent in this approach. B) not every item in the population has the same chance of being selected, as it should. C) it is usually more expensive than random sampling. D) it generally provides lower response rates than random sampling.

43) From its 32 regions, the FAA selects six regions, and then randomly audits 25 departing commercial flights in each region for compliance with legal fuel and weight requirements. This is an example of

A) simple random sampling. B) stratified random sampling. C) cluster sampling. D) judgment sampling.

44)

Which of the following is a correct statement?

A) Choosing the third person listed on every fifth page of the phone book is stratified sampling. B) An advantage of a systematic sample is that no list of enumerated data items is required. C) Convenience sampling is used to study shoppers in convenience stores. D) Judgment sampling is an example of true random sampling.

45)

Which of the following is false?

Version 1

A) Sampling error is the difference between the true parameter and the sample estimate. B) Sampling error is a result of unavoidable random variation in a sample. C) A sampling frame is chosen from the target population in a statistical study. D) The target population must first be defined by a full list or data file of all individuals.

46) When we are choosing a random sample and we do not place chosen units back into the population, we are

A) sampling with replacement. B) sampling without replacement. C) using a systematic sample. D) using a voluntary sample.

47) Which method is likely to be used by a journalism student who is casually surveying opinions of students about the university's cafeteria food for an article that she is writing for publication tomorrow?

A) simple random sample B) systematic random sample C) cluster sample D) convenience sample

48)

Which of the following is false?

A) Mail surveys are cheap but have low response rates. B) Coverage error is when respondents give untruthful answers. C) Focus groups are nonrandom but can probe issues more deeply. D) Surveys posted on popular websites suffer from selection bias.

Version 1

49)

Which is a time series variable?

A) VISA balances of 30 students on December 31 of this year B) net earnings reported by Xena Corporation for the last 10 quarters C) dollar exchange rates yesterday against 10 other world currencies D) titles of the top 10 movies in total revenue last week

50)

An observation in a data set would refer to

A) only a variable whose value is recorded by visual inspection. B) a data item whose value is numerical (as opposed to categorical). C) a single row that contains one or more observed variables. D) the values of all the variables in the entire data set.

51)

A multivariate data set contains

A) more than two observations. B) more than two categorical variables. C) more than two variables. D) more than two levels of measurement.

52) The Centers for Disease Control and Prevention (CDC) wants to estimate the average extra hospital stay that occurs when heart surgery patients experience postoperative atrial fibrillation. They divide the United States into nine regions. In each region, hospitals are selected at random within each hospital size group (small, medium, large). In each hospital, heart surgery patients are sampled according to known percentages by age group (under 50, 50 to 64, 65 and over) and gender (male, female). This procedure combines which sampling methods?

Version 1

A) systematic, simple random, and convenience B) convenience, systematic, and judgment C) cluster, stratified, and simple random D) judgment, systematic, and simple random

53)

Which statement is correct?

A) Selecting every fifth shopper arriving at a store will approximate a random sample of shoppers. B) Selecting only shoppers who drive SUVs is a stratified sampling method. C) A census is preferable to a sample for most business problems. D) Stratified samples are usually cheaper than other methods.

54)

Which is a categorical variable?

A) the brand of jeans you usually wear B) the price you paid for your last pair of jeans C) the distance to the store where you purchased your last pair of jeans D) the number of pairs of jeans that you own

55)

Which is a discrete variable?

A) the time it takes to put on a pair of jeans B) the price you paid for your last pair of jeans C) the distance to the store where you purchased your last pair of jeans D) the number of pairs of jeans that you own

Version 1

56)

A section of the population we have targeted for analysis is

A) a statistic. B) a frame. C) a sample. D) a coven.

57)

Which is not a time series variable?

A) closing checkbook balances of 30 students on December 31 of this year B) net earnings reported by Xena Corporation for the last 10 quarters C) dollar/euro exchange rates at 12 noon GMT for the last 30 days D) movie attendance at a certain theater for each Saturday last year

58)

A good Likert scale may not have

A) unequal distances between scale points. B) an odd number of scale points. C) a verbal label on each scale point. D) verbal anchors at its end points.

59) A Likert scale with an odd number of scale points between "Strongly Agree" and "Strongly Disagree"

A) cannot have equal scale distances. B) cannot have a neutral middle point. C) must have a verbal label on each scale point. D) is often used in marketing surveys.

Version 1

60) A Likert scale with an even number of scale points between "Strongly Agree" and "Strongly Disagree"

A) cannot have equal scale distances. B) is intended to prevent "neutral" choices. C) must have a verbal label on each scale point. D) is rarely used in surveys.

61)

Which statement is correct?

A) Analysts rarely consult business periodicals (e.g., Bloomberg Businessweek). B) Web searches (e.g., Google) often yield unverifiable data. C) Government data sources (e.g.,www.bls.gov) are often costly. D) Private statistical databases (e.g., CRSP) are usually free.

62)

Which statement is correct?

A) Analysts avoid business periodicals (e.g., Bloomberg Businessweek). B) Web searches (e.g., Google) yield reliable and easily verified data. C) Government data sources (e.g.,www.bls.gov) usually are free. D) Private statistical databases (e.g., CRSP) usually are free.

63)

Avalid survey is one that

Version 1

A) measures what the researcher wants to measure. B) has been approved by top management. C) is administered by a professional statistician. D) has a large number of questions.

64)

Areliable survey is one that

A) is administered by mature employees. B) has been approved by quality engineers. C) gives consistent measurements. D) has many easy questions.

65)

Because surveys are a measurement tool, they are often called

A) indicators. B) gizmos. C) instruments. D) devices.

66)

Which measurement exemplifies an interval scale but not a ratio scale?

A) weight (kilogram) of a randomly-chosen laptop computer in an office B) earnings per share of a randomly-chosen S&P 500 stock C) maximum wind speed (miles per hour) of a randomly-chosen tropical storm D) size (megabytes) of a randomly-chosen Excel spreadsheet E) water temperature (Fo) at Miami Beach on a randomly-chosen day

Version 1

67)

Categorical data have values that are described by words rather than numbers. ⊚ ⊚

68)

true false

Numerical data can be either discrete or continuous. ⊚ ⊚

true false

69)

Categorical data are also referred to as qualitative data. ⊚ true ⊚ false

70)

The number of checks processed at a bank in a day is an example of categorical data. ⊚ ⊚

71)

The number of planes per day that land at an airport is an example of discrete data. ⊚ ⊚

72)

true false

The weight of a bag of dog food is an example of discrete data. ⊚ ⊚

Version 1

true false

73) In last year’s annual report, Thompson Distributors indicated that it had 12 regional warehouses. This is an example of ordinal level data. ⊚ ⊚

74)

true false

Nominal data refer to data that can be ordered in a natural way. ⊚ ⊚

true false

75) This year, Oxnard University produced two football All-Americans. This is an example of continuous data. ⊚ ⊚

true false

76) The type of statistical test that we can perform is independent of the level of measurement of the variable of interest. ⊚ ⊚

true false

77) Your weight recorded at your annual physical would not be ratio data, because you cannot have zero weight. ⊚ ⊚

78)

true false

The level of measurement for categorical data is nominal.

Version 1

⊚ ⊚

79)

Temperature measured in degrees Fahrenheit is an example of interval data. ⊚ ⊚

80)

true false

A Likert scale on a survey is often treated as interval data. ⊚ ⊚

81)

true false

The closing price of a stock is an example of ratio data. ⊚ ⊚

true false

82) The Statistical Abstract of the United States is a huge annual compendium of data for the United States, and it is available free of charge. ⊚ ⊚

83)

Ordinal data can be treated as if it were nominal data but not vice versa. ⊚ ⊚

84)

true false

Responses on a seven-point Likert scale are usually treated as ratio data.

Version 1

⊚ ⊚

85)

Likert scales are especially important in opinion polls and marketing surveys. ⊚ ⊚

86)

true false

Judgment sampling and convenience sampling are nonrandom sampling techniques. ⊚ ⊚

90)

true false

It is better to attempt a census of a large population instead of relying on a sample. ⊚ ⊚

89)

true false

Ratio data have a zero reference point which distinguishes them from interval data. ⊚ ⊚

88)

true false

Ordinal data are data that can be ranked based on some natural characteristic of the items. ⊚ ⊚

87)

true false

A problem with judgment sampling is that the sample may not reflect the population.

Version 1

⊚ ⊚

true false

91)

When the population is large, a sample is often preferable to a census. ⊚ true ⊚ false

92)

Sampling error is avoidable by choosing the sample scientifically. ⊚ ⊚

true false

93) If we want to estimate the percentage of drivers under the age of 25 who own a vehicle then our target population should include drivers between the ages of 20–30. ⊚ true ⊚ false

94)

A sampling frame is the group from which the sample is drawn. ⊚ ⊚

95)

A parameter is a measure that describes a sample. ⊚ ⊚

96)

true false

A statistic is a measure that summarizes a sample.

Version 1

⊚ ⊚

true false

97) By taking a systematic sample, in which we select every 50th shopper arriving at a specific store, we are approximating a random sample of shoppers at that store. ⊚ ⊚

true false

98) A worker collecting data from every other shopper who leaves a store is taking a simple random sample of customer opinion. ⊚ ⊚

true false

99) Creating a list of people by taking the third name listed on every 10th page of the phone book is an example of convenience sampling. ⊚ ⊚

100)

true false

Internet surveys posted on popular websites have no bias because anyone can reply. ⊚ ⊚

true false

101) Analysis of month-by-month changes in stock market prices during the most recent recession would require the use of time series data. ⊚ true ⊚ false

Version 1

102)

A cluster sample is a type of stratified sample that is based on geographical location. ⊚ ⊚

103)

true false

An advantage of a systematic sample is that no list of enumerated data items is required. ⊚ ⊚

true false

104) Telephone surveys often have a low response rate and fail to reach the desired population. ⊚ ⊚

105)

Mail surveys are attractive because of their high response rates. ⊚ ⊚

106)

true false

A problem with convenience sampling is that the target population is not well-defined. ⊚ ⊚

true false

107) If you randomly sample 50 students about their favorite places to eat, the data collected would be referred to as cross-sectional data.

Version 1

⊚ ⊚

108)

The number of FedEx shipping centers in each of 50 cities would be ordinal level data. ⊚ ⊚

109)

true false

A bivariate data set has only two observations on a variable. ⊚ ⊚

113)

true false

Each row in a multivariate data matrix is an observation (e.g., an individual response). ⊚ ⊚

112)

true false

Different variables are usually shown as columns of a multivariate data set. ⊚ ⊚

111)

true false

Internet surveys posted on popular websites suffer from nonresponse bias. ⊚ ⊚

110)

true false

Running times for 3,000 runners in a 5k race would be a multivariate data set.

Version 1

⊚ ⊚

114)

Running times for 500 runners in a 5k race would be a univariate data set. ⊚ ⊚

115)

true false

A list of the salaries, ages, and years of experience for 50 CEOs is a multivariate data set. ⊚ ⊚

true false

116)

The daily closing price of Apple stock over the past month would be a time series. ⊚ true ⊚ false

117) data.

The number of words on 50 randomly chosen textbook pages would be cross-sectional ⊚ ⊚

true false

118) A Likert scale with an even number of scale points between "Strongly Agree" and "Strongly Disagree" is intended to prevent "neutral" choices. ⊚ ⊚

119)

true false

Private statistical databases (e.g., CRSP) are usually free.

Version 1

⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 02_7e_Doane 1) B 2) D 3) C 4) D 5) A 6) C 7) D 8) C 9) D 10) A 11) A 12) D 13) B 14) D 15) C 16) C 17) B 18) C 19) A 20) B 21) A 22) B 23) C 24) D 25) D 26) D Version 1

27) B 28) D 29) A 30) C 31) A 32) D 33) D 34) D 35) A 36) B 37) C 38) D 39) C 40) A 41) C 42) B 43) C 44) B 45) D 46) B 47) D 48) B 49) B 50) C 51) C 52) C 53) A 54) A 55) D 56) B Version 1

57) A 58) A 59) D 60) B 61) B 62) C 63) A 64) C 65) C 66) E 67) TRUE 68) TRUE 69) TRUE 70) FALSE 71) TRUE 72) FALSE 73) FALSE 74) FALSE 75) FALSE 76) FALSE 77) FALSE 78) TRUE 79) TRUE 80) TRUE 81) TRUE 82) FALSE 83) TRUE 84) FALSE 85) TRUE 86) TRUE Version 1

87) TRUE 88) FALSE 89) TRUE 90) TRUE 91) TRUE 92) FALSE 93) FALSE 94) TRUE 95) FALSE 96) TRUE 97) TRUE 98) FALSE 99) FALSE 100) FALSE 101) TRUE 102) TRUE 103) TRUE 104) TRUE 105) FALSE 106) TRUE 107) TRUE 108) FALSE 109) TRUE 110) TRUE 111) TRUE 112) FALSE 113) FALSE 114) TRUE 115) TRUE 116) TRUE Version 1

117) TRUE 118) TRUE 119) FALSE

Version 1

CHAPTER 3 1) The can be used to differentiate the "vital few" causes of quality problems from the "trivial many" causes of quality problems.

A) histogram. B) scatter plot. C) pareto chart. D) dot plot.

Which is not a characteristic of a dot plot?

A) simplicity B) legibility C) wide bins D) dot stacking

Which display is most likely to reveal association betweenX andY?

A) dot plot B) scatter plot C) histogram D) pareto chart

4) Which criterion is least likely to be used in choosing bins (classes) in a frequency distribution?

Version 1

A) Following Sturges’ Rule. B) Selecting "nice" class (bin) limits. C) Using aesthetic judgment. D) Starting the first bin at zero.

Which of the following is true?

A) Line charts are not used for cross-sectional data. B) Line charts are useful for visualizing categorical data. C) Line charts are generally preferred instead of bar charts. D) Pie charts can often be used instead of line charts.

Histograms generally do not reveal the

A) exact data range. B) degree of symmetry. C) degree of skewness. D) relative frequencies.

A column chart would be least suitable to display which data?

A) annual compensation of 500 company CEOs B) U.S. exports to its six largest trading partners C) Exxon-Mobil’s quarterly sales for the last four years D) one-year CD interest rates paid by the eight largest U.S. banks

A line chart would not be suitable to display which data?

Version 1

A) U.S. oil imports from OPEC nations for the last 20 years B) annual compensation of the top 50 CEOs C) Exxon-Mobil’s quarterly sales data for the last five years D) daily stock market closing prices of Microsoft for the past month

Which is not a tip for effective column charts?

A) Time usually goes on the horizontal axis. B) Column height should be proportional to the frequency of the column’s category displayed. C) Label data values at the top of each column unless graphing lots of data. D) The zero origin rule may be waived for financial reports.

10)

Which is not a tip for effective line charts?

A) Line charts are ideal to display cross-sectional data. B) Numerical labels are omitted on a line chart if there are many data values. C) Omit data markers (e.g., squares, triangles) when there are many data values. D) Thick lines make it harder to see exact data values.

11)

Which is a reason for using a log scale for time series data?

A) It helps compare growth in time series of dissimilar magnitude. B) General business audiences find it easier to interpret a log scale. C) On a log scale, equal distances represent equal dollar amounts. D) The axis labels are usually easier to read in log units.

Version 1

12)

Which is a not a characteristic of pie charts?

A) Pie charts can only convey a general idea of the data values. B) Pie charts are ineffective when they have too many slices. C) Exploded and 3D pie charts will allow more "slices." D) Pie chart data always represent parts of a whole (e.g., market share).

13)

Excel's rotated 3D bar charts charts

A) are generally preferred to plain 2D charts. B) should be avoided despite their visual appeal. C) are generally preferred to line charts. D) show data values more clearly than column charts.

14)

Which is not a reason why pie charts are popular in business?

A) They can convey a general idea of the data to a nontechnical audience. B) They can display major changes in parts of a whole (e.g., market share). C) They are more precise than line charts, despite their low visual impact. D) They can be labeled with data values to facilitate interpretation.

15)

Which data would be suitable for a pie chart?

A) Whirlpool Corporation’s sales revenue for the last five years B) Oxnard University student enrollment by category (undergraduate, masters, doctoral) C) average SAT scores for entering students at 10 major U.S. universities D) annual U.S. toy imports from China over the past decade

Version 1

16)

Which data would be suitable for a pie chart?

A) percent vote in the last election by party (Democrat, Republican, Other) B) retail prices of six major brands of color laser printers C) labor cost per vehicle for 10 major world automakers D) prices paid by 10 students for their accounting textbooks

17)

Which data would be suitable for a pie chart?

A) average starting salary of MBA graduates from eight ivy-league universities B) APR interest rates charged by the top five U.S. credit cards C) last semester’s average GPA for students in seven majors in a business school D) the number of U.S. primary care clinics by type (urban, suburban, rural)

18)

Scatter plots are

A) preferred in visualizing trends over time. B) able to reveal causal relationships. C) often fitted with a linear equation in Excel. D) applicable mainly to discrete data.

19)

Which is not a characteristic of an effective summary table?

A) The main point should be clear within 10 seconds. B) Data to be compared should be displayed in rows, not columns. C) Data should be rounded to three or four significant digits. D) Use space instead of lines to separate columns.

Version 1

20)

Effective summary tables generally

A) have very detailed column headings and footnotes. B) round their data to three or four significant digits. C) use plenty of heavy vertical lines to separate the columns. D) have the raw data listed in a footnote for clarity.

21)

Pivot tables

A) are similar in purpose to simple 2D pie charts. B) show how the data "pivot" around a point. C) show cross-tabulations of data. D) are not really tables at all.

22)

Which of the following is least useful in visualizing categorical data?

A) bar chart B) pie chart C) line chart D) pareto chart

23) Which type of chart would you use to show the percent of purchases at Starbuck’s by payment type (Cash, Gift Card, Starbuck’s Card, Apple Pay, Google Pay, Other)?

Version 1

A) pie chart or Bar chart B) histogram C) pyramid chart D) line chart

24)

We would use a pivot table to

A) cross-tabulate frequencies of occurrence of two variables. B) rotate the data around a central point. C) establish cause-and-effect between x and y. D) display the data in a 3D scatter plot.

25)

Which is not considered a deceptive graphical technique?

A) nonzero origin B) elastic graph proportions C) dramatic title D) axis demarcations

26)

Which is not considered a deceptive graphical technique?

A) undefined units B) 2D graphs C) authority figures D) distracting pictures

27)

Which deceptive graphical technique can lead to distorting relative size?

Version 1

A) vague source B) using bold colors C) nonzero origin D) unlabeled data points

28)

Which is not a poor graphing technique?

A) gratuitous pictures B) labeled axis scales C) 3D bar charts D) rotated axis

29)

Which of these deficiencies would be considered amajor visual deception on a graph?

A) vague or unclear source B) using more than one color or font C) bar widths proportional to bar height D) using a dramatic graph title

30)

Which is not a characteristic of a log scale for time series data?

A) Log scales are useful when data change by an order of magnitude. B) The distance from 5 to 50 is the same as the distance from 50 to 500. C) On a log scale, equal distances represent equal ratios. D) Log scales are familiar to the average reader.

31)

Which is not a characteristic of using a log scale to display time series data?

Version 1

A) A log scale helps if we are comparing changes in two time series of dissimilar magnitude. B) General business audiences find it easier to interpret a log scale. C) If you display data on a log scale, equal distances represent equal ratios. D) Log scales are used when the data vary over a range by more than an order of magnitude.

32) This histogram shows Chris’s golf scores in his last 77 rounds at Devil’s Ridge. Which is not a correct statement?

A) the number of bins is consistent with Sturges’ Rule B) the histogram has a noticeable bimodal shape C) the modal class is 78 < 80 D) about 15 percent of his scores are in the interval 74 < 76

33)

Which is not revealed on a scatter plot?

Version 1

A) pairs of observed ( xi, yi) data values B) nonlinear relationships between X and Y C) missing data values due to nonresponses D) unusual data values (outliers)

34)

The distribution pictured below is

A) bimodal and skewed right. B) bimodal and skewed left. C) skewed right. D) skewed left.

35)

The distribution pictured below is

A) bimodal and skewed right. B) bimodal and skewed left. C) skewed right. D) skewed left.

Version 1

36)

The graph below illustrates which deceptive technique?

A) poor y-axis scale B) area trick C) unclear grid lines D) dramatic title

37)

Which is a characteristic of a histogram’s bars?

A) The bar widths reveal the cumulative frequencies of data values. B) The bar widths indicate class intervals, and their areas indicate frequencies. C) The bar widths show class intervals, and their heights indicate frequencies. D) The bar widths are an exact multiple of the sample size.

38)

Below is a frequency distribution of earnings of 50 contractors in a country. Earnings (thousands) 1 to 10 11 to 20 20 to 30 31 to 40

Version 1

Number of Contractors 2 7 12 15

41 to 50 50 to 60

8 6

Regarding this distribution, which of the following is correct? A) The frequency distribution contains too many class intervals. B) The class interval limits are ambiguous. C) Too few classes were chosen. D) The class intervals are too wide.

39)

Bob found an error in the following frequency distribution. What is it? Earnings (thousands) 1 to 10 11 to 20 25 to 30 31 to 40 44 to 50

Number of Contractors 2 6 8 12 6

A) The class limits are overlapping too much. B) The classes are not collectively exhaustive. C) There are too many classes by Sturges’ Rule. D) The first class must start at 0.

40)

The point halfway between the bin limits in a frequency distribution is known as the

A) bin midpoint. B) bin limit. C) bin frequency. D) bin width.

41)

When using a dot plot with a small sample, which is least apparent?

Version 1

A) dispersion of data values within the array B) the overall shape of the distribution C) central tendency of data in the data set D) location of data values within the array

42)

If you have 256 data points, how many classes (bins) would Sturges’ Rule suggest?

A) 6 B) 7 C) 8 D) 9

43)

If you have 32 data points, how many classes (bins) would Sturges’ Rule suggest?

A) 5 B) 6 C) 7 D) 8

44)

Which statement is not true concerning Sturges’ Rule?

A) It proposes adding one class (bin) to the histogram for each extra observation. B) If you double the sample size, you should add one class. C) Its purpose is to tell how many classes (bins) to use in a frequency distribution. D) It is only a guideline and may be overruled by other considerations.

45)

To classify prices from 62 recent home sales, Sturges’ Rule would recommend

Version 1

A) 7 classes. B) 8 classes. C) 9 classes. D) 10 classes.

46)

A histogram can be defined as a chart whose A) column widths show the cumulative frequencies of data values. B) column widths indicate class intervals and whose areas indicate frequencies. C) column widths show class intervals and whose heights indicate frequencies. D) column heights represent the value of each data point.

47)

An open-ended bin (e.g., "50 and over") might be seen in a frequency distribution when

A) some data values are not integers. B) data values are nonnumerical. C) extremely large data values exist. D) some data are missing.

48)

The width of a bin in a frequency distribution is known as the

A) midpoint. B) class limit. C) bin frequency. D) class interval.

Version 1

49) A data set has 5,500 observations. When the data are represented in a relative frequency distribution, the relative frequency of a given interval is 0.15. The frequency in this interval is equal to

A) 4,675. B) 800. C) 675. D) 825.

50) A population has 75 observations. One class interval has a frequency of 15 observations. The relative frequency in this category is

A) 0.20. B) 0.10. C) 0.15. D) 0.75.

51) Below is a sorted stem-and-leaf diagram for the measured speeds (miles per hour) of 49 randomly chosen vehicles on highway I-80 in Nebraska. How many vehicles were traveling exactly the speed limit (70 mph)? Stem unit = 10 Leaf unit = 1 Frequency 1 1 17 19 7 4 49

Version 1

Stem 4 5 6 7 8 9

Leaf 9 5 0 1 2 2 2 4 5 5 5 5 6 6 8 8 9 9 9 0 1 1 1 2 3 3 3 4 5 6 6 6 7 7 8 9 9 9 0 1 3 3 5 5 7 0 1 2 2

A) 0 B) 1 C) 19 D) It is impossible to tell.

52) Below is a sorted stem-and-leaf diagram for the measured speeds (miles per hour) of 49 randomly chosen vehicles on highway I-80 in Nebraska. What is the highest observed speed? Stem unit = 10 Leaf unit = 1 Frequency 1 1 17 19 7 4 49

Stem 4 5 6 7 8 9

Leaf 9 5 0 1 2 2 2 4 5 5 5 5 6 6 8 8 9 9 9 0 1 1 1 2 3 3 3 4 5 6 6 6 7 7 8 9 9 9 0 1 3 3 5 5 7 0 1 2 2

A) 92 B) 90 C) 87 D) It is impossible to tell.

53) Below is a sorted stem-and-leaf diagram for the measured speeds (miles per hour) of 49 randomly chosen vehicles on highway I-80 in Nebraska. What is the mode? Stem unit = 10 Leaf unit = 1 Frequency 1 1 17 19 7

Version 1

Stem 4 5 6 7 8

Leaf 9 5 0 1 2 2 2 4 5 5 5 5 6 6 8 8 9 9 9 0 1 1 1 2 3 3 3 4 5 6 6 6 7 7 8 9 9 9 0 1 3 3 5 5 7

4 49

0 1 2 2

A) 62 B) 79 C) 65 D) It is impossible to tell.

54) Below is a sorted stem-and-leaf diagram for the measured speeds (miles per hour) of 49 randomly chosen vehicles on highway I-80 in Nebraska. What is the fourth slowest speed in the sorted data array? Stem unit = 10 Leaf unit = 1 Frequency 1 1 17 19 7 4 49

Stem 4 5 6 7 8 9

Leaf 9 5 0 1 2 2 2 4 5 5 5 5 6 6 8 8 9 9 9 0 1 1 1 2 3 3 3 4 5 6 6 6 7 7 8 9 9 9 0 1 3 3 5 5 7 0 1 2 2

A) 61 B) 60 C) 55 D) It is impossible to tell.

55) Below is a sorted stem-and-leaf diagram for the measured speeds (miles per hour) of 49 randomly chosen vehicles on highway I-80 in Nebraska. Which is the modal class? Stem unit = 10 Leaf unit = 1 Frequency 1 1

Version 1

Stem 4 5

Leaf 9 5

17 19 7 4 49

6 7 8 9

0 1 2 2 2 4 5 5 5 5 6 6 8 8 9 9 9 0 1 1 1 2 3 3 3 4 5 6 6 6 7 7 8 9 9 9 0 1 3 3 5 5 7 0 1 2 2

A) 60 but less than 70. B) 70 but less than 80. C) 80 but less than 90. D) It is impossible to determine.

56) A statistician prepared a bar chart showing, in descending order, the frequency of six underlying causes of general aviation accidents (pilot error, mechanical problems, disorientation, miscommunication, controller error, other). What would we call this type of chart?

A) pivot table B) pareto chart C) log scale chart D) frequency polygon

57) Which chart would be most appropriate to display PepsiCo’s quarterly revenue for the most recent 20 quarters?

A) line chart B) Pareto chart C) scatter plot D) frequency polygon

58) Which chart would be most appropriate to display the frequency of 10 common patient symptoms in COVID-19 cases that arrive in hospital emergency facilities?

Version 1

A) line chart B) Pareto chart C) scatter plot D) frequency polygon

59) Which chart would be most appropriate to compare last year’s CEO compensation in 50 companies with percent operating profit margin in those companies?

A) line chart B) Pareto chart C) scatter plot D) frequency polygon

60)

Which chart would be appropriate to display percent operating profit in 500 corporations? A) line chart B) Pareto chart C) scatter plot D) histogram

61) Which chart would be appropriate to compare staffed bed count in the three major hospitals in Las Vegas?

A) line chart B) Pareto chart C) pie chart D) histogram

Version 1

62)

It is easier to read the data values on a 3D column chart than on a 2D column chart. ⊚ ⊚

63)

The column chart cannot be used if you are plotting time series data. ⊚ ⊚

64)

true false

Excel's rotated column chart is generally preferred to a plain 2D column chart. ⊚ ⊚

67)

true false

The Pareto chart is used to display the "vital few" causes of problems. ⊚ ⊚

66)

true false

The line chart is appropriate for categorical (qualitative) data. ⊚ ⊚

65)

true false

Excel's rotated column charts make it easier to read the data values. ⊚ ⊚

Version 1

true false

68)

Dot plots are similar to histograms with many bins (classes). ⊚ ⊚

true false

69) Compared to a dot plot, we lose some detail when we present data in a frequency distribution. ⊚ ⊚

true false

70) Association between two paired quantitative variables (X, Y) is best shown on a stacked column chart. ⊚ ⊚

71)

Log scales are common because most people are familiar with them. ⊚ ⊚

72)

true false

Sturges’ Rule should override judgment about the "right" number of histogram bins. ⊚ ⊚

73)

true false

Sturges’ Rule is merely a suggestion, not an ironclad requirement. ⊚ ⊚

Version 1

true false

74)

There is only one right number of bins for a histogram. ⊚ ⊚

75)

Excel’s default histograms typically need modification before incorporating into a report. ⊚ ⊚

76)

true false

A histogram can be used to identify potential outliers. ⊚ ⊚

true false

77) Stem-and-leaf displays, dot plots, and histograms can all be used to show skewness in a distribution. ⊚ ⊚

78)

Excel’s 3D pie charts are usually clearer than 2D pie charts. ⊚ ⊚

79)

true false

A common error with pie charts is using too few "slices."

Version 1

⊚ ⊚

80)

A pie chart can generally be used instead of a bar chart. ⊚ ⊚

81)

true false

Dot plots may not reveal the shape of a distribution when the sample is small. ⊚ ⊚

85)

true false

Pie charts are useful in displaying frequencies that sum to a total. ⊚ ⊚

84)

true false

Pie charts are attractive when we only need a general idea of data values. ⊚ ⊚

83)

true false

A column chart can sometimes be used instead of a line chart for time series data. ⊚ ⊚

82)

true false

Scatter plots are used to visualize association in samples of paired data ( X, Y).

Version 1

⊚ ⊚

true false

86) The zero origin rule may be waived for column or line charts if the objective is to visualize relative magnitudes over time. ⊚ ⊚

87)

In a bimodal histogram, the two highest bars will have the same height. ⊚ ⊚

88)

true false

A frequency distribution usually has equal bin widths. ⊚ ⊚

91)

true false

A dot plot would be useful in visualizing scores on an exam in a class of 30 students. ⊚ ⊚

90)

true false

A frequency distribution is a tabulation of n data values into classes called bins. ⊚ ⊚

89)

true false

Line charts are not used for cross-sectional data.

Version 1

⊚ ⊚

92)

A scatter plot is best for visualizing trends over time. ⊚ ⊚

93)

true false

A scatter plot requires two paired quantitative variables (i.e., not categorical data). ⊚ ⊚

true false

94) The number of bins in this histogram (caffeine content in mg/oz for 65 soft drinks) is consistent with Sturges’ Rule.

⊚ ⊚

Version 1

true false

95) This dot plot (burglary rates per 100,000 persons in 350 U.S. cities) shows a distribution that is skewed to the left (negatively skewed).

⊚ ⊚

true false

96) Frequency distributions should always have bin limits to ensure that bins have equal width. ⊚ ⊚

true false

97) Except for the Y-axis scaling, a histogram will look the same if we use relative frequencies instead of raw frequencies (with the same bin limits). ⊚ ⊚

true false

98) Except for the y-axis scaling, a histogram will look the same if we use relative frequencies instead of raw frequencies (with the same bin limits). ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 03_7e_Doane 1) C 2) C 3) B 4) D 5) A 6) A 7) A 8) B 9) D 10) A 11) A 12) C 13) B 14) C 15) B 16) A 17) D 18) C 19) B 20) B 21) C 22) C 23) A 24) A 25) D 26) B Version 1

27) C 28) B 29) C 30) D 31) B 32) A 33) C 34) A 35) D 36) B 37) C 38) B 39) B 40) A 41) B 42) D 43) B 44) A 45) A 46) C 47) C 48) D 49) D 50) A 51) B 52) A 53) C 54) A 55) B 56) B Version 1

57) A 58) B 59) C 60) D 61) C 62) FALSE 63) FALSE 64) FALSE 65) TRUE 66) FALSE 67) FALSE 68) TRUE 69) TRUE 70) FALSE 71) FALSE 72) FALSE 73) TRUE 74) FALSE 75) TRUE 76) TRUE 77) TRUE 78) FALSE 79) FALSE 80) FALSE 81) TRUE 82) TRUE 83) TRUE 84) TRUE 85) TRUE 86) FALSE Version 1

87) FALSE 88) TRUE 89) TRUE 90) TRUE 91) TRUE 92) FALSE 93) TRUE 94) FALSE 95) FALSE 96) TRUE 97) TRUE 98) TRUE

Version 1

CHAPTER 4 1)

The coefficient of variation is

A) measured on a scale from 0 to 100. B) a unit-free statistic. C) helpful when the sample means are zero. D) a measure of correlation for two variables.

Which is not an advantage of the method of medians to find Q1 and Q3?

A) Ease of interpolating quartile positions. B) Ease of application in small data sets. C) Intuitive definitions without complex formulas. D) Same method as Excel's =QUARTILE.EXC function.

Which is a characteristic of the mean as a measure of center?

A) Deviations from the mean do not sum to zero when there are extreme values. B) It is less reliable than the mode when the data are continuous. C) It utilizes all the information in a sample. D) It is usually equal to the median in business data.

The position of the median is

A) n/2 in any sample. B) n/2 if n is even. C) n/2 if n is odd. D) ( n+1)/2 in any sample.

Version 1

Which is a characteristic of the trimmed mean as a measure of center?

A) It is similar to the mean if there are offsetting high and low extremes. B) It is especially helpful in a small sample. C) It does not require sorting the sample. D) It is basically the same as the midrange.

Which is not a characteristic of the geometric mean as a measure of center?

A) It is similar to the mean if the data are skewed right. B) It mitigates the effects of large data values. C) It is useful in business data to calculate average growth rates. D) It cannot be calculated when the data contain negative or zero values.

Which is a characteristic of the mode as a measure of center?

A) It is similar to the mean if the data are skewed right. B) It mitigates the effects of large data values. C) It is best used to describe continuous data. D) It is best used to describe integer data with many repetitive values.

Which of the following isnot true about a distribution’s shape?

Version 1

A) If the mean and median are the same, the distribution is most likely symmetric. B) If the mean is much greater than the median, the distribution is most likely skewed right. C) If the distribution is symmetric, there must not be any outliers. D) It the mean is much less than the median, there could be outliers on the lower end of the distribution.

Which is not a characteristic of the standard deviation?

A) It is always the square root of the variance. B) It is not applicable when data are continuous. C) It can be calculated when the data contain negative or zero values. D) Its physical interpretation is not as easy as the MAD.

10)

Chebyshev’s Theorem

A) applies to all samples. B) applies only to samples from a normal population. C) gives a narrower range of predictions than the Empirical Rule. D) is based on Sturges’ Rule for data classification.

11)

Which of the following is not a valid description of an outlier?

A) A data value beyond the outer fences. B) A data value that is very unusual. C) A data value that lies below Q1 or above Q3. D) A data value several standard deviations from the mean.

Version 1

12)

If samples are from a normal distribution with μ = 100 and σ = 10, we expect

A) about 68 percent of the data within 90 to 110. B) about 68 percent of the data within 80 to 120. C) about 95 percent of the data within 70 to 130. D) about half the data to exceed 75.

13) In a sample of 10,000 observations from a normal population, how many would you expect to lie beyond three standard deviations of the mean?

A) About 27. B) About 100. C) About 127. D) None of them.

14)

Which is the Excel formula for the standard deviation of a sample array named Data?

A) =STDEV.S(Data). B) =STANDEV(Data). C) =STDEV.P(Data). D) =SUM(Data)/(COUNT(Data)-1).

15)

Which is not true of an outlier?

Version 1

A) It is likely to be from a different population. B) It suggests an error in recording the data. C) It is best discarded to get a better mean. D) It is an anomaly that may tell the researcher something.

16)

Estimating the mean from grouped data will tend to be most accurate when

A) observations are distributed uniformly within classes. B) there are few classes with wide class limits. C) the sample is not very large and bins are wide. D) the standard deviation is large relative to the mean.

17)

Which is true of the kurtosis of a distribution?

A) A distribution that is flatter than a normal distribution (i.e., thicker tails) is mesokurtic. B) A distribution that is more peaked than a normal distribution (i.e., thinner tails) is platykurtic. C) It is risky to assess kurtosis if the sample size is less than 50. D) The expected range of the kurtosis coefficient increases as n increases.

18)

Which is true of skewness?

A) In business data, positive skewness is unusual. B) In a negatively skewed distribution, the mean is likely to exceed the median. C) Skewness often is evidenced by one or more outliers in one end of the distribution. D) The expected range of Excel’s skewness coefficient increases as n increases.

Version 1

19)

Which is not true of the Empirical Rule?

A) It applies to any distribution. B) It can be applied to fewer distributions than Chebyshev’s Theorem. C) It assumes that the distribution of data follows a bell-shaped, normal curve. D) It predicts more observations within μ ± kσ than Chebyshev’s Theorem.

20)

Which is a correct statement concerning the median?

A) In a left-skewed distribution, we expect that the median will exceed the mean. B) The sum of the deviations around the median is zero. C) The median is an observed data value in any data set. D) The median is halfway between Q1 and Q3 on a box plot.

21)

Which statement is true?

A) The mode is a common measure of center with nominal data. B) Outliers distort the mean, but not the standard deviation. C) Business and economic data are rarely skewed to the right. D) If we sample a normal population, the sample skewness coefficient is exactly 0.

22) Exam scores in a small class were 10, 10, 20, 20, 40, 60, 80, 80, 90, 100, 100. For this data set, which statement is incorrect concerning measures of center?

A) The median is 60.00. B) The mode is not helpful. C) The 5 percent trimmed mean would be awkward. D) The geometric mean is 35.05.

Version 1

23) Exam scores in a small class were 0, 50, 50, 70, 70, 80, 90, 90, 100, 100. For this data set, which statement is incorrect concerning measures of center?

A) The median is 70. B) The mode is not helpful. C) The geometric mean is useless. D) The mean is 70.

24) Exam scores in a random sample of students were 0, 50, 50, 70, 70, 80, 90, 90, 90, 100. Which statement is incorrect?

A) The standard deviation is 29.61. B) The data are slightly left-skewed. C) The midrange and mean are almost the same. D) The third quartile is 90.

25) For U.S. adult males, the mean height is 178 cm with a standard deviation of 8 cm and the mean weight is 84 kg with a standard deviation of 8 kg. Elmer is 170 cm tall and weighs 70 kg. It is most nearly correct to say that

A) Elmer’s weight is more unusual than his height. B) Elmer is heavier than he is tall. C) Height and weight have the same degree of variation. D) Height has more variation than weight.

John scored 85 on Prof. Hardtack’s exam ( Q1 = 40 and Q3 = 60). Based on the fences, 26) which is correct?

Version 1

A) John is an extreme outlier. B) John is an outlier. C) John is not an outlier. D) John is in the 85th percentile.

John scored 35 on Prof. Johnson’s exam ( Q1 = 70 and Q3 = 80). Based on the fences, 27) which is correct?

A) John is unusual but not an outlier. B) John is an outlier. C) John is neither unusual nor an outlier. D) John is in the 30th percentile.

28) A population consists of the following data: 7, 11, 12, 18, 20, 22, 25. The population variance is

A) 6.07 B) 36.82 C) 5.16 D) 22.86

29)

Consider the following data: 6, 7, 17, 51, 3, 17, 23, and 69. The range and the median are

A) 69 and 17.5. B) 66 and 17.5. C) 66 and 17. D) 69 and 17.

Version 1

30)

When a sample has an odd number of observations, the median is the

A) observation in the center of the data array. B) average of the two observations in the center of the data array. C) value of the most frequent observation. D) average of Q1 and Q3.

31) As a measure of variability, compared to the range, an advantage of the standard deviation is that it

A) is calculated easily through the use of a formula. B) considers only the data values in the middle of the data array. C) describes the distance between the highest and lowest values. D) considers all data values.

32)

Which two statistics offer robust measures of center when outliers are present?

A) Mean and mode. B) Median and trimmed mean. C) Midrange and geometric mean. D) Variance and standard deviation.

33)

Which Excel function is designed to calculate thez-score for a column of data?

Version 1

A) =STANDARDIZE B) =NORM.DIST C) =STDEV.P D) =AVEDEV

34) Which Excel function would be least useful to calculate the quartiles for a column of data?

A) =STANDARDIZE B) =PERCENTILE.EXC C) =QUARTILE.EXC D) =RANK

35) The boxplot shows the spending for a sample of 50 breakfast customers of McDonald’s. Which statement is least likely to be correct?

A) The median is very close to the midhinge. B) The median purchase is slightly less than $5. C) About 75 percent of the customers spend less than $7. D) The mean is a reasonable measure of center.

Version 1

36) VenalCo Market Research surveyed 50 individuals who have more than 10,000 followers on Instagram, revealing the age distribution shown below. Which statement is least defensible?

A) The mean age probably exceeds the median age. B) The mode would be a reasonable measure of center. C) The data are somewhat skewed to the left. D) Popular Instagram accounts tend to be younger individuals.

37)

Given a sample of three items ( X = 4, 6, 5), which statement is incorrect?

A) The geometric mean is 5.2. B) The standard deviation is 1. C) The coefficient of variation is 20 percent. D) The quartiles are useless.

38) A sample of customers from Barnsboro National Bank shows an average account balance of $315 with a standard deviation of $87. A sample of customers from Wellington Savings and Loan shows an average account balance of $8350 with a standard deviation of $1800. Which statement about account balances is correct?

Version 1

A) Barnsboro Bank has more relative variation. B) Wellington S&L has more relative variation. C) Both have the same relative variation. D) The maximum account balance for Barnsboro Bank cannot be greater than $576.

39)

Histograms are best used to

A) provide a visual estimate of the standard deviation. B) show the quartiles of the data set. C) assess the shape of the distribution. D) reveal the interquartile range of the data set.

40)

The

shows the relationship between two variables.

A) box plot. B) bar chart. C) histogram. D) scatter plot.

41)

If the mean and median of a population are the same, then its distribution is

A) skewed right. B) skewed left. C) symmetric. D) None of these could apply.

42)

In the following data set {7, 5, 0, 2, 7, 15, 5, 2, 7, 18, 7, 3, 0}, the value 7 is

Version 1

A) the mean. B) the mode. C) both the mode and median. D) both the mean and mode.

43)

The median of 600, 800, 1000, 1200 is

A) 800 B) 1000 C) 900 D) 950

44) The 25th percentile for waiting time in a doctor’s office is 19 minutes. The 75th percentile is 31 minutes. The interquartile range (IQR) is

A) 12 minutes. B) 16 minutes. C) 22 minutes. D) impossible to determine without knowing n.

45) The 25th percentile for waiting time in a doctor’s office is 19 minutes. The 75th percentile is 31 minutes. Which is incorrect regarding the fences?

A) The upper inner fence is 49 minutes. B) The upper outer fence is 67 minutes. C) A waiting time of 45 minutes exceeds the upper inner fence. D) A waiting time of 70 minutes would be an outlier.

Version 1

46) When using Chebyshev’s Theorem, the minimum percentage of sample observations that will fall within two standard deviations of the mean will be the percentage within two standard deviations if a normal distribution is assumed (Empirical Rule).

A) smaller than. B) greater than. C) the same as.

47)

Which distribution is least likely to be skewed to the right by high values?

A) Annual incomes of n passengers on a flight from New York to London B) Weekend gambling losses of n customers at a major casino C) Accident damage losses by n renters of an auto rental company D) Cost of a plain McDonald’s hamburger in n U.S. cities

48) Based on daily measurements, Bob’s weight has a mean of 200 pounds with a standard deviation of 16 pounds, while Mary’s weight has a mean of 125 pounds with a standard deviation of 15 pounds. Who has the smaller relative variation?

A) Bob B) Mary C) They are the same.

49) Frieda is 67 inches tall and weighs 135 pounds. Women her age have a mean height of 65 inches with a standard deviation of 2.5 inches and a mean weight of 125 pounds with a standard deviation of 10 pounds. In relative terms, it is correct to say that

Version 1

A) Frieda is taller and thinner than women in her age group. B) for this group of women, weight has lesser variation than height. C) Frieda’s weight is more unusual than height and the weight has greater variation than height. D) the variation coefficient exceeds 10 percent for both height and weight.

50)

Which statement is false?

A) The coefficient of variation cannot be used when the mean is zero. B) The standard deviation is in the same units as the mean (e.g., kilograms). C) The mean from a frequency tabulation may differ from the mean from raw data. D) The skewness coefficient is zero in a sample from any normal distribution.

51)

The values of xmin and xmax can be inferred accurately except in a

A) box plot. B) dot plot. C) histogram. D) scatter plot.

52)

Which of the following statements is likely to be true?

A) The median personal income of California taxpayers would probably be near the mean. B) The interquartile range offers a measure of income inequality among California residents. C) For income, the sum of squared deviations about the mean is negative about half the time. D) For personal incomes in California, outliers in either tail would be equally likely.

Version 1

53)

Which statistics offer robust (resistant to outliers) measures of center?

A) Mean, midrange, mode. B) Median, midhinge, trimmed mean. C) Trimmed mean, midrange, midhinge. D) Mean, mode, quartiles.

54)

The Empirical Rule says that

A) about 95 percent of the data are beyond one standard deviation from the mean. B) about 99 percent of the data are beyond one standard deviation from the mean. C) about 32 percent of the data are within one standard deviation from the mean. D) about 32 percent of the data are beyond one standard deviation from the mean.

55) Three randomly chosen Seattle students were asked how many round trips they made to Canada last year. Their replies were 3, 4, 5. The geometric mean is

A) 3.877 B) 4.000 C) 3.915 D) 4.422

56) Three randomly chosen California students were asked how many times they drove to Mexico last year. Their replies were 4, 5, 6. The geometric mean is

Version 1

A) 3.87 B) 5.00 C) 5.42 D) 4.93

57) Three randomly chosen Colorado students were asked how many times they went rock climbing last month. Their replies were 5, 6, 7. The standard deviation is

A) 1.212 B) 0.816 C) 1.000 D) 1.056

58) Patient survival times after a certain type of surgery have a very right-skewed distribution due to a few high outliers. Consequently, which statement is most likely to be correct?

A) Median > Midrange. B) Mean < Median. C) Mean > Midrange. D) Mean > Trimmed Mean.

59) So far this year, stock A has had a mean price of $6.58 per share with a standard deviation of $1.88, while stock B has had a mean price of $10.57 per share with a standard deviation of $3.02. Which stock is more volatile?

A) Stock A. B) Stock B. C) They are the same. D) Both would be considered a poor investment.

Version 1

60)

Outliers can be indicated using fences on a

A) box plot. B) dot plot. C) histogram. D) Pareto chart.

61)

Which is not a measure of variability?

A) Mean absolute deviation (MAD). B) Range. C) Coefficient of variation. D) Trimmed mean.

62) Twelve randomly chosen students were asked how many times they had missed class during a certain semester, with this result: 3, 2, 1, 2, 1, 5, 9, 1, 2, 3, 3, 10. The geometric mean is

A) B) 2.604 C) 1.517 D)

63) Twelve randomly chosen students were asked how many times they had missed class during a certain semester, with this result: 3, 2, 1, 2, 1, 5, 9, 1, 2, 3, 3, 10. The median is

Version 1

A) 7.0 B) 3.0 C) 3.5 D) 2.5

64)

One disadvantage of the range is that

A) only extreme values are used in its calculation. B) it is expressed in different units than the mean. C) it does not exist for some data sets. D) it is undefined if any X values are 0 or negative.

65)

Which is a characteristic of the standard deviation?

A) It is not greatly affected by outliers. B) It is measured in the same units as the mean. C) It measures dispersion around the median. D) It has a natural, concrete meaning.

66) Twelve randomly chosen students were asked how many times they had missed class during a certain semester, with this result: 2, 1, 5, 1, 1, 3, 4, 3, 1, 1, 5, 18. For this sample, the geometric mean is

A) 2.158 B) 1.545 C) 2.376 D) 3.017

Version 1

67) Twelve randomly chosen students were asked how many times they had missed class during a certain semester, with this result: 2, 1, 5, 1, 1, 3, 4, 3, 1, 1, 5, 18. For this sample, the median is

A) 2 B) 3 C) 3.5 D) 2.5

68) Twelve randomly chosen students were asked how many times they had missed class during a certain semester, with this result: 2, 1, 5, 1, 1, 3, 4, 3, 1, 1, 5, 18. For this sample, which measure of center is least representative of the "typical" student?

A) Mean B) Median C) Mode D) Midrange

69) Here are statistics on order sizes of Megalith Construction Supply’s shipments of two kinds of construction materials last year. Girders Mean Standard Deviation

160 48

Rivets 2800 702

Which order sizes have greater relative variability? A) Girders. B) Rivets. C) They are the same. D) Cannot be determined without knowing n.

Version 1

70)

The quartiles of a distribution are most clearly revealed in which display?

A) Box plot. B) Scatter plot. C) Histogram. D) Dot plot.

71)

The sum of the deviations around the mean is

A) greater than zero if data are right-skewed. B) smaller when the units are smaller (e.g., milligrams versus kilograms). C) always zero. D) dependent on the sample size.

72)

What does the graph below (profit/sales ratios for 25 Fortune 500 companies) reveal?

A) That the median exceeds the mean. B) That the data are slightly left-skewed. C) That the data are slightly right-skewed. D) That the distribution is bell-shaped.

73)

Find the sample correlation coefficient for the following data. X

Y 3

Version 1

7 5 9 11 13 19 21

12 13 10 17 23 39 38

A) .8911 B) .9132 C) .9822 D) .9556

The heights of male students in a certain statistics class range from Xmin = 61 to Xmax = 74) 79. Applying the Empirical Rule, a reasonable estimate of σ would be

A) 2.75 B) 3.00 C) 3.25 D) 3.50

75) A reporter for the campus paper asked five randomly chosen students how many occupants, including the driver, ride to school in their cars. The responses were 1, 1, 1, 1, 6. The coefficient of variation is

A) 25 percent. B) 250 percent. C) 112 percent. D) 100 percent.

Version 1

76) A smooth distribution with one mode is negatively skewed (skewed to the left). The median of the distribution is $65. Which of the following is a reasonable value for the distribution mean?

A) $76 B) $54 C) $81 D) $65

77) In a positively skewed distribution, the percentage of observations that fall below the median is:

A) about 50 percent. B) less than 50 percent. C) more than 50 percent. D) cannot tell without knowing n.

78)

Which is a weakness of the mode?

A) It does not apply to qualitative data. B) It is inappropriate for continuous data. C) It is hard to calculate when n is small. D) It is usually about the same as the median.

79)

The mode is least appropriate for

Version 1

A) continuous data. B) categorical data. C) discrete data. D) Likert scale data.

80) Craig operates a part-time snow-plowing business using a 2002 GMC 2500 HD extended cab short box truck. This box plot of Craig’s MPG on 195 tanks of gas does not support which statement?

A) There are several outliers. B) This is a very right-skewed distribution. C) Most MPG values are concentrated in a narrow range. D) The interquartile range is less than 2 MPG.

81)

Estimate the mean exam score for the 50 students in Professor Axolotl’s class.

Score 40 but less than 50 50 but less than 60 60 but less than 70 70 but less than 80 80 but less than 90 Total

f 6 18 14 9 3 50

A) 59.2 B) 62.0 C) 63.5 D) 64.1

Version 1

82) A survey of salary increases received during a recent year by 44 working MBA students is shown. Find the approximate mean percent raise. Percent Increase 0 but less than 2 2 but less than 4 4 but less than 6 6 but less than 10 Total

Number 3 4 10 27 44

A) 6.56 B) 6.74 C) 5.90 D) 6.39

83) The following frequency distribution shows the amount earned yesterday by employees of a large Las Vegas casino. Estimate the mean daily earnings. Earnings (dollars) 50 < 75 75 < 100 100 < 125 125 < 150 150 < 175

Frequency 10 15 60 40 10

A) $112.50 B) $125.01 C) $105.47 D) $117.13

84)

The following table is the frequency distribution of parking fees for a day: Fee (dollars) 6.00 < 6.50 6.50 < 7.00 7.00 < 7.50

Version 1

Number of Garages 5 8 10

7.50 < 8.00

What is the mean parking fee?

A) $7.07 B) $6.95 C) $7.00 D) $7.25

85)

Find the standard deviation of this sample: 4, 7, 9, 12, 15.

A) 4.550 B) 3.798 C) 4.278 D) 2.997

86) The 25th percentile for waiting time in a doctor’s office is 10 minutes. The 75th percentile is 30 minutes. Which is incorrect regarding the fences?

A) The upper inner fence is 60 minutes. B) The upper outer fence is 90 minutes. C) A waiting time of 45 minutes would be an outlier. D) The lower fences are not relevant in this problem.

87) Five homes were recently sold in Oxnard Acres. Four of the homes sold for $400,000, while the fifth home sold for $2.5 million. Which measure of central tendency best represents a typical home price in Oxnard Acres?

Version 1

A) The mean or median. B) The median or mode. C) The mean or mode. D) The midrange or mean.

88) In Tokyo, construction workers earn an average of ¥420,000 (yen) per month with a standard deviation of ¥20,000, while in Hamburg, Germany, construction workers earn an average of €3,200 (euros) per month with a standard deviation of €57. Which statement is most correct about a worker making ¥460,000 per month in Tokyo and one earning €3,300 per month in Hamburg?

A) The workers are the same in relative terms. B) The Tokyo worker is relatively better off. C) The Hamburg worker is relatively better off. D) Neither worker is earning more than the median salary in their country.

89)

Which statement is false? Explain.

A) If μ = 52 and σ = 15, then X = 80 would be an outlier. B) Ifμ = 640 andσ = 128 from a normal population, then about 68 percent of the values will be between 512 and 768. C) If μ = 640 and σ = 128, then the coefficient of variation is 20 percent. D) Ifμ = 52 andσ = 15 from a normal population, then about 16% of the data would be greater than 67.

90)

Which is not a measure of variability?

Version 1

A) Mean absolute deviation (MAD). B) Standard deviation. C) Midhinge. D) Interquartile range.

91)

If Q1 = 150 and Q3 = 250, the upper fences (inner and outer) are

A) 450 and 600. B) 350 and 450. C) 400 and 550. D) impossible to determine without more information.

92)

Do variables X and Y have the same correlation in both scatter plots?

Version 1

A) No, figure A shows weaker correlation. B) No, figure B shows weaker correlation. C) They are approximately the same relationship. D) Their correlations are similar in magnitude but opposite in direction.

93) Which of the following statements is likely to apply to the incomes of 50 randomly chosen taxpayers in California?

A) The median income would probably be near the mean. B) The midhinge would be a robust measure of center. C) The sum of squared deviations about the mean would be negative. D) Outliers in either tail would be equally likely.

94) A certain health maintenance organization (HMO) examined the number of office visits by each of its members in the last year. For this data set, we would anticipate that the geometric mean would be

A) a reasonable measure of center. B) zero because some HMO members would not have an office visit. C) too high because the distribution is likely to be skewed to the left. D) negative because some data values would be below the mean.

95) Three randomly chosen Colorado students were asked how many times they went rock climbing last month. Their replies were 5, 6, 7. The coefficient of variation is

A) 16.7 percent. B) 13.6 percent. C) 20.0 percent. D) 35.7 percent.

Version 1

96) The mean of a population is 50 and the median is 40. Which histogram is best fits this population?

A) Sample A. B) Sample B. C) Sample C. D) None of these could apply.

97)

If Excel's sample skewness coefficient is positive, which of the following is not correct?

A) We know that the population is skewed to the right. B) We know that the population is symmetric. C) We should consult a table of skewness percentiles that takes sample size into consideration.

98)

If Excel's sample kurtosis coefficient is negative, which of the following is not correct?

A) We know that the population is platykurtic. B) We know that the population is leptokurtic. C) We should consult a table of percentiles that takes sample size into consideration.

Version 1

99)

The midhinge lies halfway between

A) xmin and xmax. B) Q1 and Q3. C) the mean and the median. D) the inner fences.

100)

Which is not a characteristic of the midhinge?

A) It lies halfway between Q1 and Q3. B) It is used to detect asymmetry. C) It is equal to the median in a symmetric data set. D) It is strongly affected by outliers.

101)

Which measure of is unit-free?

A) =CORREL(Xdata, YData) B) =COVAR.P(XData,YData) C) =COVAR.S(Xdata,YData) D) =AVEDEV(Data)

102)

To calculate the Pearson 2 coefficient of skewness Sk2 for a sample, we need the

A) mean, median, and mode. B) mean, median, and standard deviation. C) mean, mode, and standard deviation. D) mode and quartiles.

Version 1

103)

If μ = 52, σ = 15, and X = 80 the z-score would be A) 1.87 B) −0.93 C) −1.87 D) 0.93

104)

Ifμ = 52,σ = 15, andX = 40 thez-score would be

A) 6.0 B) 0.80 C) −0.80 D) −6.0

105)

Ifxmax = 150 andxmin = 90 and the population is normal, one could estimate σ to be A) cannot estimate sigma without a sample data set. B) 6 C) 10 D) 15

106) Bob has a part-time job applying lawn fertilizer. He recorded the time required for a lawn treatment for last week’s service calls: 28, 31, 24, 36, 44, 40, 72, 39, 32, 56, 22, 37, 41, 51, 38, 27, 29. Are there outliers?

Version 1

A) There are 4 outliers. B) No. C) Insufficient information to answer. D) There is one unusual value which some might consider an outlier.

107) A data set with two values that are tied for the highest number of occurrences is called bimodal. ⊚ ⊚

108)

The midrange is not greatly affected by outliers. ⊚ ⊚

109)

true false

The second quartile is the same as the median. ⊚ ⊚

true false

110) A trimmed mean may be preferable to a mean as a measure of center when a data set has extreme values. ⊚ ⊚

111)

true false

One benefit of the box plot is that it clearly displays the standard deviation.

Version 1

⊚ ⊚

112)

It is inappropriate to apply the Empirical Rule to a population that is right-skewed. ⊚ ⊚

113)

true false

The sum of the deviations around the mean is always zero. ⊚ ⊚

117)

true false

When data are right-skewed, we expect the median to be greater than the mean. ⊚ ⊚

116)

true false

Given the data set 2, 5, 10, 6, 3, the median value is 3. ⊚ ⊚

115)

true false

Given the data set 10, 5, 2, 6, 3, 4, 20, the median value is 5. ⊚ ⊚

114)

true false

The midhinge is a robust measure of center when there are outliers.

Version 1

⊚ ⊚

true false

118) Chebyshev’s Theorem says that at most 50 percent of the data lie within 2 standard deviations of the mean. ⊚ ⊚

true false

119) Chebyshev’s Theorem says that at least 95 percent of the data lie within 2 standard deviations of the mean. ⊚ ⊚

true false

120) If there are 19 data values, the median will have 10 values above it and 9 below it since n is odd. ⊚ ⊚

121)

If there are 20 data values, the median will be halfway between two data values. ⊚ ⊚

122)

true false

In a left-skewed distribution, we expect that the median will be greater than the mean. ⊚ ⊚

Version 1

true false

123) If the standard deviations of two samples are the same, so are their coefficients of variation. ⊚ ⊚

true false

124) A certain health maintenance organization (HMO) examined the number of office visits by its members in the last year. This data set would probably be skewed to the left due to low outliers. ⊚ ⊚

true false

125) A certain health maintenance organization examined the number of office visits by its members in the last year. For this data set, the mean is probably not a very good measure of a “typical” person’s office visits. ⊚ ⊚

true false

126) Referring to this box plot of ice cream fat content, the median seems more “typical” of fat content than the midrange as a measure of center.

⊚ ⊚

Version 1

true false

127)

Referring to this box plot of ice cream fat content, the mean would exceed the median.

⊚ ⊚

128)

Referring to this box plot of ice cream fat content, the skewness would be negative.

⊚ ⊚

129)

true false

Referring to this graph of ice cream fat content, the second quartile is between 60 and 61.

⊚ ⊚

Version 1

true false

130)

The range as a measure of variability is very sensitive to extreme data values. ⊚ ⊚

true false

131) In calculating the sample variance, the sum of the squared deviations around the mean is divided by n − 1 to avoid underestimating the unknown population variance. ⊚ ⊚

true false

132) Data values that fall beyond ±2 standard deviations from the mean are often considered unusual or outliers. ⊚ ⊚

133)

The Empirical Rule assumes that the distribution of data follows a normal curve. ⊚ ⊚

134)

true false

The Empirical Rule can be applied to any distribution, unlike Chebyshev’s theorem. ⊚ ⊚

true false

135) When applying the Empirical Rule to a distribution of grades, if a student scored one standard deviation below the mean, then she would be at the 25th percentile of the distribution. Version 1

⊚ ⊚

136)

true false

Kurtosis cannot be judged accurately by looking at a histogram. ⊚ ⊚

true false

137) A platykurtic distribution is more sharply peaked (i.e., thinner tails) than a normal distribution. ⊚ ⊚

true false

138) A leptokurtic distribution is more sharply peaked (i.e., thinner tails) than a normal distribution. ⊚ ⊚

139)

true false

A positive kurtosis coefficient in Excel suggests a leptokurtic shape of a distribution. ⊚ ⊚

true false

140) A sample consists of the following data: 7, 11, 12, 18, 20, 22, 43. Using the "three standard deviation" criterion, the last observation ( X = 43) would be considered an outlier. ⊚ ⊚

Version 1

true false

141) The geometric mean can be calculated from a data set that has both positive and negative values. ⊚ ⊚

true false

142) If a data set can be assumed to have a normal distribution then a quick way to estimate σ is (xmax−xmin)/6. ⊚ ⊚

143)

Given anx = 12,µ = 15, andσ = 4, the standardizedz−score = −0.75. ⊚ ⊚

144)

true false

Given anx = 12,µ = 15, andσ = 4, the standardizedz-score = +0.75. ⊚ ⊚

145)

true false

To calculateMAD on Excel one would use the AVEDEV function. ⊚ ⊚

true false

146) The mean absolute deviation is preferred to the standard deviation because it is more complicated to calculate and is therefore a more precise measure of variation. Version 1

⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 04_7e_Doane 1) B 2) D 3) C 4) D 5) A 6) A 7) D 8) C 9) B 10) A 11) C 12) A 13) A 14) A 15) C 16) A 17) C 18) C 19) A 20) A 21) A 22) D 23) A 24) C 25) A 26) C Version 1

27) B 28) B 29) C 30) A 31) D 32) B 33) A 34) A 35) D 36) A 37) A 38) A 39) C 40) D 41) C 42) B 43) C 44) A 45) C 46) A 47) D 48) A 49) C 50) D 51) C 52) B 53) B 54) D 55) C 56) D Version 1

57) C 58) D 59) C 60) A 61) D 62) B 63) D 64) A 65) B 66) C 67) D 68) D 69) A 70) A 71) C 72) C 73) D 74) B 75) C 76) B 77) A 78) B 79) A 80) B 81) B 82) D 83) D 84) A 85) C 86) C Version 1

87) B 88) B 89) A 90) C 91) C 92) D 93) B 94) B 95) A 96) A 97) C 98) C 99) B 100) D 101) A 102) A 103) A 104) C 105) C 106) D 107) TRUE 108) FALSE 109) TRUE 110) TRUE 111) FALSE 112) TRUE 113) TRUE 114) FALSE 115) FALSE 116) TRUE Version 1

117) TRUE 118) FALSE 119) FALSE 120) FALSE 121) TRUE 122) TRUE 123) FALSE 124) FALSE 125) TRUE 126) TRUE 127) FALSE 128) TRUE 129) TRUE 130) TRUE 131) TRUE 132) TRUE 133) TRUE 134) FALSE 135) FALSE 136) TRUE 137) FALSE 138) TRUE 139) TRUE 140) FALSE 141) FALSE 142) TRUE 143) TRUE 144) FALSE 145) TRUE 146) FALSE Version 1

Version 1

CHAPTER 5 1)

Events A and B are mutually exclusive when

A) their joint probability is zero. B) they are independent events. C) P( A) P( B) = 0 D) P( A) P( B) = P( A | B)

If two events are complementary, then we know that

A) the sum of their probabilities is one. B) the joint probability of the two events is one. C) their intersection has a nonzero probability. D) they are independent events.

Regarding probability, which of the following is correct?

A) When events A and B are mutually exclusive, then P( A ∩ B) = P( A) + P( B). B) The union of events A and B consists of all outcomes in the sample space that are contained in both event A and event B. C) When two events A and B are independent, the joint probability of the events can be found by multiplying the probabilities of the individual events. D) The probability of the union of two events can exceed one.

Independent events A and B would be consistent with which of the following statements?

Version 1

A) P(A) = .3,P(B) = .5,P(A ∩ B) = .4. B) P(A) = .4,P(B) = .5,P(A ∩ B) = .2. C) P(A) = .5,P(B) = .4,P(A ∩ B) = .3. D) P(A) = .4,P(B) = .3,P(A ∩ B) = .5.

5) Find the probability that either event A or B occurs if the chance of A occurring is .5, the chance of B occurring is .3, and events A and B are independent.

A) .80 B) .15 C) .65 D) .85

Regarding the rules of probability, which of the following statements is correct?

A) If A and B are independent events, then P( B) = P( A) P( B). B) The probabilities of mutually exclusive events sum to one. C) The probability of A or its complement equals one. D) If event A occurs, then its complement will also occur.

7) Within a given population, 22 percent of the people are smokers, 57 percent of the people are males, and 12 percent are males who smoke. If a person is chosen at random from the population, what is the probability that the selected person is either a male or a smoker?

A) .67 B) .79 C) .22 D) .43

Version 1

8) Information was collected on those who attended the opening of a new movie. The analysis found that 56 percent of the moviegoers were female, 26 percent were under age 25, and 17 percent were females under the age of 25. Find the probability that a moviegoer is either female or under age 25.

A) .79 B) .82 C) .65 D) .50

Given the contingency table shown here, find P( V). County Macomb (M) Oakland (O) Wayne (W) Col Total

Cell Phone Service Provider Sprint (S) AT&T (A) Verizon (V) 17 25 8 19 38 13 24 37 19 60

100

Row Total 50 70 80 200

A) .20 B) .40 C) .50 D) .80

10)

Given the contingency table shown here, find P( V | W).

County Macomb (M) Oakland (O) Wayne (W) Col Total

Version 1

Cell Phone Service Provider Sprint (S) AT&T (A) Verizon (V) 17 25 8 19 38 13 24 37 19 60

100

Row Total 50 70 80 200

A) .4000 B) .0950 C) .2375 D) .5875

11) Given the contingency table shown here, find the probability P( V'), that is, the probability of the complement of V. County Macomb (M) Oakland (O) Wayne (W) Col Total

Cell Phone Service Provider Sprint (S) AT&T (A) Verizon (V) 17 25 8 19 38 13 24 37 19 60

100

Row Total 50 70 80 200

A) .30 B) .50 C) .80 D) .15

12)

Given the contingency table shown here, find P( W ∩ S).

County Macomb (M) Oakland (O) Wayne (W) Col Total

Cell Phone Service Provider Sprint (S) AT&T (A) Verizon (V) 17 25 8 19 38 13 24 37 19 60

100

Row Total 50 70 80 200

A) .12 B) .30 C) .40 D) .58

Version 1

13)

Given the contingency table shown here, find P( A or M).

County Macomb (M) Oakland (O) Wayne (W)

Cell Phone Service Provider Sprint (S) AT&T (A) Verizon (V) 17 25 8 19 38 13 24 37 19

Col Total

100

Row Total 50 70 80

200

A) .2500 B) .7500 C) .6250 D) .1250

Given the contingency table shown here, find P( A2).

14) B1 B2 B3

Col Total

Row Total

12 14 18

26 28 32

42 44 47

68 64 72

148 150 169

133

204

467

A) .1842 B) .1766 C) .8163 D) .0578

Given the contingency table shown here, find P( A3 ∩ B2).

15) B1 B2 B3

Col Total

Version 1

Row Total

12 14 18

26 28 32

42 44 47

68 64 72

148 150 169

133

204

467

A) .3212 B) .2933 C) .0942 D) .1006

Given the contingency table shown here, find P( A2 | B3).

16) B1 B2 B3

Col Total

Row Total

12 14 18

26 28 32

42 44 47

68 64 72

148 150 169

133

204

467

A) .0685 B) .1893 C) .3721 D) .1842

Given the contingency table shown here, find P( A1 or B2).

17) B1 B2 B3

Col Total

Row Total

12 14 18

26 28 32

42 44 47

68 64 72

148 150 169

133

204

467

Row Total

A) .0933 B) .3182 C) .0300 D) .3854

18)

Given the contingency table shown here, find P( A1 ∩ A2). A1

Version 1

B1 B2 B3 Col Total

12 14 18

26 28 32

42 44 47

68 64 72

148 150 169

133

204

467

A) .00 B) .09 C) .28 D) .38

Given the contingency table shown here, find the probability that either event A2 or event 19) B2 will occur. B1 B2 B3 Col Total

Row Total

12 14 18

26 28 32

42 44 47

68 64 72

148 150 169

133

204

467

A) .4454 B) .5054 C) .0600

20)

Given the contingency table shown here, find P( B).

Absences Under 2 days (B) 2 or more days (B') Column Total

Version 1

Age Under 25 (A) 50 30

25 or More (A') 40 80

Row Total 90 110

120

200

A) .85 B) .25 C) .45 D) .22

21)

Given the contingency table shown here, find P( A or B).

Absences Under 2 days (B) 2 or more days (B') Column Total

Age Under 25 (A) 50 30

25 or More (A') 40 80

Row Total 90 110

120

200

Age Under 25 (A) 50 30

25 or More (A') 40 80

Row Total 90 110

120

200

A) .25 B) .85 C) .60 D) .42

22)

Given the contingency table shown here, find P( B | A).

Absences Under 2 days (B) 2 or more days (B') Column Total

A) .250 B) .555 C) .855 D) .625

Version 1

23) Given the contingency table shown here, what is the probability that a randomly chosen employee who is under age 25 would be absent 2 or more days?

Absences Under 2 days (B) 2 or more days (B') Column Total

Age Under 25 (A) 50 30

25 or More (A') 40 80

Row Total 90 110

120

200

A) .625 B) .375 C) .150 D) .273

24) Oxnard Casualty wants to ensure that their e-mail server has 99.98 percent reliability. They will use several independent servers in parallel, each of which is 95 percent reliable. What is the smallest number of independent file servers that will accomplish the goal?

A) 1 B) 2 C) 3 D) 4

25) Which statement is most consistent with the contingency table shown here? Survey question: Do you plan on retiring or keep working when you turn 65? Employee Management (M) Line worker (L) Total

Version 1

Retire (R) 13 39 52

Work (W) 18 54

Total 31 93

124

A) The decision to retire appears independent of the employee type. B) The decision to retire does not appear independent of the employee type. C) The probability of a manager retiring at age 65 is .25. D) The probability of retiring at age 65 is .25.

26) Given the contingency table shown here, find the probability that a randomly chosen employee is a line worker who plans to retire at age 65. Survey question: Do you plan on retiring or keep working when you turn 65? Employee Management (M) Line worker (L) Total

Retire (R) 13 39

Work (W) 18 54

Total 31 93

124

A) .227 B) .419 C) .750 D) .315

27)

Given the contingency table shown here, find P( R ∩ L).

Survey question: Do you plan on retiring or keep working when you turn 65? Employee Management (M) Line worker (L) Total

Retire (R) 13 39 52

Work (W) 18 54

Total 31 93

124

A) .250 B) .315 C) .425 D) .850

Version 1

28)

Given the contingency table shown here, find P( W | M).

Survey question: Do you plan on retiring or keep working when you turn 65? Employee Management (M) Line worker (L) Total

Retire (R) 13 39

Work (W) 18 54

Total 31 93

124

A) .145 B) .250 C) .581 D) .687

29)

Given the contingency table shown here, find P( L or W).

Survey question: Do you plan on retiring or keep working when you turn 65? Employee Management (M) Line worker (L) Total

Retire (R) 13 39 52

Work (W) 18 54

Total 31 93

124

A) .750 B) .588 C) .435 D) .895

30) Ramjac Company wants to set up k independent file servers, each capable of running the company’s intranet. Each server has average "uptime" of 98 percent. What must k be to achieve 99.999 percent probability that the intranet will be "up"?

Version 1

A) 1 B) 2 C) 3 D) 4

31) Given the contingency table shown here, what is the probability that a mother in the study smoked during pregnancy? Mother’s Education Below High School High School Some College College Degree Col Total

Smoked during Pregnancy

Didn’t Smoke during Pregnancy

Row Total

393 560 121 48

640 1,370 635 550

1,033 1,930 756 598

1,122

3,195

4,317

A) .2599 B) .3174 C) .5000 D) .7401

32) Given the contingency table shown here, what is the probability that a mother smoked during pregnancy if her education level was below high school? Mother’s Education Below High School High School Some College College Degree Col Total

Version 1

Smoked during Pregnancy 393 560 121 48

Didn’t Smoke during Pregnancy 640 1,370 635 550

Row Total

1,122

3,195

4,317

1,033 1,930 756 598

A) .2385 B) .0907 C) .3503 D) .3804

33) Given the contingency table shown here, what is the probability that a mother smoked during pregnancy and had a college degree? Mother’s Education Below High School High School Some College College Degree Col Total

Smoked during Pregnancy 393 560 121 48

Didn’t Smoke during Pregnancy 640 1,370 635 550

Row Total

1,122

3,195

4,317

1,033 1,930 756 598

A) .0111 B) .0428 C) .0803 D) .2385

34) Given the contingency table shown here, what is the probability that a mother smoked during pregnancy or that she graduated from college? Mother’s Education Below High School High School Some College College Degree Col Total

Version 1

Smoked during Pregnancy 393 560 121 48

Didn’t Smoke during Pregnancy 640 1,370 635 550

Row Total

1,122

3,195

4,317

1,033 1,930 756 598

A) .0111 B) .2591 C) .3873 D) .7850

35) Given the contingency table shown here, if a mother attended some college but did not have a degree, what is the probability that she did not smoke during her pregnancy? Mother’s Education Below High School High School Some College College Degree Col Total

Smoked during Pregnancy 393 560 121 48

Didn’t Smoke during Pregnancy 640 1,370 635 550

Row Total

1,122

3,195

4,317

1,033 1,930 756 598

A) .2736 B) .8399 C) .8752 D) .9197

36) Given the contingency table shown here, find the probability if the mother with some college is selected at random who smoked during pregnancy. Mother’s Education Below High School High School Some College College Degree Col Total

Version 1

Smoked during Pregnancy 393 560 121 48

Didn’t Smoke during Pregnancy 640 1,370 635 550

Row Total

1,122

3,195

4,317

1,033 1,930 756 598

A) .1078 B) .1746 C) .1601 D) .1117

37) Given the contingency table shown here, if a survey participant is selected at random, what is the probability he/she is an undergrad who favors the change to a quarter system?

Opinion:

Group Surveyed Undergrads (U) Graduates (G)

Faculty (F)

Row Total

Oppose Change (N) Favor Change (S)

120

Col Total

100

200

A) .270 B) .135 C) .338 D) .756

38) Given the contingency table shown here, if a faculty member is chosen at random, what is the probability he/she opposes the change to a quarter system?

Opinion:

Group Surveyed Undergrads (U) Graduates (G)

Faculty (F)

Row Total

Oppose Change (N) Favor Change (S)

120

Col Total

100

200

Version 1

A) .10 B) .25 C) .40 D) .60

39) Given the contingency table shown here, what is the probability that a participant selected at random is a graduate student who opposes the change to a quarter system?

Opinion:

Group Surveyed Undergrads (U) Graduates (G)

Faculty (F)

Row Total

Oppose Change (N) Favor Change (S)

120

Col Total

100

200

A) .135 B) .250 C) .375 D) .540

40) Given the contingency table shown here, what is the probability that a student attends a public school in a rural area? What type of school do you attend? Location Inner City (I) Suburban (S) Rural (R) Col Total

Version 1

Public (P) Religious (R) Other Private (O) 35 15 20 45 10 25 25 5 5 105

Row Total 70 80 35 185

A) .238 B) .714 C) .135 D) .567

41) Given the contingency table shown here, if a randomly chosen student attends a religious school, what is the probability the location is rural? What type of school do you attend? Location Inner City (I) Suburban (S) Rural (R) Col Total

Public (P) Religious (R) Other Private (O) 35 15 20 45 10 25 25 5 5 105

Row Total 70 80 35 185

A) .142 B) .162 C) .167 D) .333

42) Given the contingency table shown here, if a randomly chosen student attends school in an inner-city location, what is the probability that it is a public school? What type of school do you attend? Location Inner City (I) Suburban (S) Rural (R) Col Total

Version 1

Public (P) Religious (R) Other Private (O) 35 15 20 45 10 25 25 5 5 105

Row Total 70 80 35 185

A) .189 B) .333 C) .500 D) .567

43)

Given the contingency table shown here, find P( E).

Gender Male (M) Female (F) Col Total

Accounting (A) 210 150

Major General Management (G) 180 160

360

340

Economics (E)

Row Total

140 160

530 470

300

1000

Economics (E)

Row Total

140 160

530 470

300

1000

A) .180 B) .300 C) .529 D) .641

44)

Given the contingency table shown here, find P( E | F).

Gender Male (M) Female (F) Col Total

Accounting (A) 210 150

Major General Management (G) 180 160

360

340

A) .160 B) .300 C) .340 D) .533

Version 1

45)

Given the contingency table shown here, find P( A ∩ M).

Gender Male (M) Female (F) Col Total

Accounting (A) 210 150

Major General Management (G) 180 160

360

340

Economics (E)

Row Total

140 160

530 470

300

1000

Economics (E)

Row Total

140 160

530 470

300

1000

A) .210 B) .360 C) .396 D) .583

46)

Given the contingency table shown here, find P( F or G).

Gender Male (M) Female (F) Col Total

Accounting (A) 210 150

Major General Management (G) 180 160

360

340

A) .160 B) .470 C) .650 D) .810

47) Given the contingency table shown here, find the probability that a randomly chosen individual is a female economics major.

Gender

Version 1

Accounting

Major General

Economics (E)

Row Total

Male (M) Female (F) Col Total

(A) 210 150

Management (G) 180 160

140 160

530 470

360

340

300

1000

A) .3404 B) .4700 C) .1600 D) .5333

48) Debbie has two stocks, X and Y. Consider the following events: X = the event that the price of stock X has increased Y = the event that the price of stock Y has increased The event "the price of stock X has increased and the price of stock Y has not increased" may be written as

A) X ' ∩ Y B) X or Y ʹ C) X ∩ Y ʹ D) X or Y

49)

If P( A | B) = .40 and P( B) = .30, find P( A ∩ B).

A) .171 B) .525 C) .571 D) .120

Version 1

50) A company is producing two types of ski goggles. Thirty percent of the production is of type A, and the rest is of type B. Five percent of all type A goggles are returned within 10 days after the sale, whereas only two percent of type B are returned. If a pair of goggles is returned within the first 10 days after the sale, the probability that the goggles returned are of type B is

A) .014 B) .140 C) .070 D) .483

51) Given the contingency table shown here, find the joint probability that a call sampled at random out of this population is local and 2 to 5 minutes long. Call Length (minutes) Type of Phone Call Local Long Distance Total

0 to 1 150 170

2 to 5 250 120

6+ 100 10

Total 500 300

320

370

110

800

A) .5000 B) .3125 C) .4000 D) .4625

52) Given the contingency table shown here, if a call is sampled at random, find the marginal probability that the call is long distance. Call Length (minutes) Type of Phone Call Local Long Distance Total

Version 1

0 to 1 150 170

2 to 5 250 120

6+ 100 10

Total 500 300

320

370

110

800

A) .3750 B) .6250 C) .4000 D) 300/500

53) If a call is sampled at random, the conditional probability that the call is not "6+" minutes long given that it is a long distance call is Call Length (minutes) Type of Phone Call Local Long Distance Total

0 to 1 150 170

2 to 5 250 120

6+ 100 10

Total 500 300

320

370

110

800

A) 120/300 B) 10/300 C) .9667 D) .6667

54) The following table gives a classification of the 10,000 shareholders of Oxnard Xylophone Distributors, Incorporated. A few numbers are missing from the table. Given that a shareholder holding 500 to 999 shares is picked, there is a .625 probability that the shareholder will be a woman. Consequently, what is the number of men holding 1000 or more shares? Number of Shares Held Shareholders Men Women Joint Accounts Total

Version 1

0 to 499 3,000

500 to 999

1,000+

2,000

Total 4,000 4,800

1,000

200

1,200

5,000

4,000

1,000

10,000

A) 1,000 B) 250 C) 7,500 D) 500

55)

The following table shows the survival experience of 1,000 males who retire at age 65: Age 65 70 75 80 85

Number of Males Surviving 1,000 907 775 596 383

Based on these data, the probability that a 65-year-old male will survive to age 75 is A) .775 − .596 = .179 B) .907 − .775 = .132 C) 1 − .775 = .225 D) .775

56)

If P( A ∩ B) = .50, can P( A) = .20?

A) Only if P( A | B) = .10. B) Not unless P( B) = .30. C) Only if P( B ∩ A) = .60. D) If P( A) = .20, then P( A ∩ B) cannot equal .50.

57)

The following relationship always holds true for events A and B in a sample space.

Version 1

A) P( A | B) = P( B | A) B) P( A ∩ B) = P( A | B) P( B) C) P( A | B) = P( B | A) P( A) D) P(B) =P(A |B)P(A)

58) The following probabilities are given about events A and B in a sample space: P( A) = .30, P( B) = .40, P( A or B) = .60. We can say that

A) P( A ∩ B) = .70. B) P( A) = P( A ∩ B). C) P( A ∩ B) = .10. D) A and B are independent events.

59)

If P( A) = .35, P( B) = .60, and P( A or B) = .70, then

A) A and B are mutually exclusive. B) P( A ∩ B) = .15. C) P( A ∩ B) = .25. D) P( A ∩ B) = .35.

60)

The following table shows the survival experience of 1,000 males who retire at age 65: Age 65 70 75 80 85

Version 1

Number of Males Surviving 1,000 907 775 596 383

Based on these data, the probability that a 75-year-old male will survive to age 80 is A) .596 B) 1 − .596 = .404 C) 1 − .775 = .225 D) .769

61)

Given the contingency table shown here, find P( G | M).

Vehicle Type Car (C) Minivan (M) Full-Size Van (F) SUV (V) Truck (T) Col Total

Somerset (S) Oakland (O) Great Lakes (G) 44 49 36 21 15 18 2 3 3 19 27 26 14 6 17 100

100

Row Total 129 54 8 72 37 300

A) .1800 B) .0450 C) .3333 D) .1350

62)

Given the contingency table shown here, find P( V or S).

Vehicle Type Car (C) Minivan (M) Full-Size Van (F) SUV (V) Truck (T) Col Total

Version 1

Somerset (S) Oakland (O) Great Lakes (G) 44 49 36 21 15 18 2 3 3 19 27 26 14 6 17 100

100

Row Total 129 54 8 72 37 300

A) .5100 B) .4300 C) .0475 D) .4775

63)

Given the contingency table shown here, find P( V | S).

Vehicle Type Car (C) Minivan (M) Full-Size Van (F) SUV (V) Truck (T) Col Total

Somerset (S) Oakland (O) Great Lakes (G) 44 49 36 21 15 18 2 3 3 19 27 26 14 6 17 100

100

Row Total 129 54 8 72 37 300

A) .2639 B) .1900 C) .0475 D) .4144

64) The manager of Ardmore Pharmacy knows that 25 percent of the customers entering the store buy prescription drugs, 65 percent buy over-the-counter drugs, and 18 percent buy both types of drugs. What is the probability that a randomly selected customer will buy at least one of these two types of drugs?

A) .90 B) .85 C) .72 D) .65

65)

Two events are complementary (i.e., they are complements) if

Version 1

A) the product of their probabilities equals one. B) their probabilities sum to one. C) the joint probability of the two events equals one. D) they are independent events.

66)

Which statement is false?

A) If P( A) = .05, then the odds against event A’s occurrence are 19 to 1. B) If A and B are mutually exclusive events, then P( A or B) = 0. C) The number of permutations of five things taken two at a time is 20. D) IfA andB are mutually exclusive events, thenP(A andB) = 0.

67)

The number of unique orders in which five items ( A, B, C, D, E) can be arranged is

A) 5 B) 840 C) 120 D) 24

68) If four items are chosen at random without replacement from seven items, in how many ways can the four items be arranged, treating each arrangement as a different event (i.e., if order is important)?

A) 35 B) 840 C) 5040 D) 24

Version 1

69) How many ways can we choose three items at random without replacement from five items ( A, B, C, D, E) if the order of the selected items is not important?

A) 60 B) 120 C) 10 D) 24

70)

The value of6 C2 is

A) 15 B) 30 C) 720 D) 12

71)

The value of4 P2 is

A) 8 B) 6 C) 24 D) 12

72)

The probability that event A occurs, given that event B has occurred, is an example of:

Version 1

A) a marginal probability. B) a conditional probability. C) a joint probability. D) more than one of the above.

73) If each of two independent file servers has a reliability of 93 percent and either alone can run the website, then the overall website availability is

A) .9951 B) .8649 C) .9300 D) .9522

74) In a certain city, 5 percent of all drivers have expired licenses, 10 percent have an unpaid parking ticket, and 1 percent have both an expired license and an unpaid parking ticket. Which statement is true?

A) Having an expired license is not independent of have an unpaid parking ticket. B) Having an expired license and having an unpaid parking ticket are mutually exclusive. C) Having an expired license is independent of have an unpaid parking ticket. D) None of these three statements is true.

75) In a certain city, 5 percent of all drivers have expired licenses and 10 percent have an unpaid parking ticket. If these events are independent, what is the probability that a driver has both an expired license and an unpaid parking ticket?

Version 1

A) .010 B) .005 C) .001 D) Cannot be determined

76) If two events are collectively exhaustive, what is the probability that one or the other will occur?

A) 1.00 B) .00 C) .50 D) Cannot tell from given information.

77)

Which best exemplifies a subjective probability?

A) The probability that a female age 30 will have an accident in a week’s car rental at Hertz. B) The probability that a pair of dice will come up 7 in a given throw. C) The probability that the summer Olympic games will be held in Chicago in 2028. D) The probability that a checked bag on Flight 1872 will weigh more than 40 pounds.

78)

Which best exemplifies the classical definition of probability?

A) The probability that a male age 50 will have an accident in a week’s car rental at Alamo. B) The probability that a pair of dice will come up 7 when they are rolled. C) The probability that the winter Olympic games will be held in Europe in 2022. D) The probability that a checked bag on Flight 1872 will weigh more than 30 pounds.

Version 1

79)

Which best exemplifies the empirical definition of probability?

A) The probability that a Chinese athlete will win the diving competition in the next Olympics. B) The probability that a fair coin will come up heads when it is flipped. C) The probability that your own bank will become insolvent within 12 months. D) The probability that a checked bag on Flight 1872 will weigh less than 30 pounds.

80) From the following tree, find the probability that a randomly chosen person will get the flu vaccine and will also get the flu.

A) .10 B) .07 C) .19 D) .70

Version 1

81) From the following tree, find the probability that a randomly chosen person will not get a vaccination and will not get the flu.

A) .18 B) .60 C) .19 D) .70

82) flu.

From the following tree, find the probability that a randomly chosen person will get the

Version 1

A) .19 B) .07 C) .81 D) .70

83) At Joe’s Restaurant, 80 percent of the diners are new customers ( N), while 20 percent are returning customers ( R). Fifty percent of the new customers pay by credit card, compared with 70 percent of the regular customers. If a customer pays by credit card, what is the probability that the customer is a new customer?

A) .7407 B) .8443 C) .5400 D) .1600

84) At Dolon General Hospital, 30 percent of the patients have Medicare insurance ( M) while 70 percent do not have Medicare insurance ( M´). Twenty percent of the Medicare patients arrive by ambulance, compared with 10 percent of the non-Medicare patients. If a patient arrives by ambulance, what is the probability that the patient has Medicare insurance?

A) .2100 B) .5118 C) .4615 D) .1400

85) Which of the following is the sample space describing the time to place an order at a McDonald’s drive-thru?

Version 1

A) S = {1 min, 2 min, 3 min}. B) S = {allX such thatX ≥ 0}. C) S = {allX such that 0 ≤X ≤ 3 min}. D) S = {allX such thatX ≤ 0}.

86) Which of the following is the sample space describing the number of items ordered at a McDonald’s drive-thru?

A) S = {1, 2, 3, …}. B) S = {allX such thatX ≥ 1}. C) S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. D) S = {allX such thatX is an integer}.

87) Which of the following is the sample space describing the number of cracked eggs in a full dozen carton?

A) S = {1, 2, 3, …}. B) S = {1, 2, 3, …, 11, 12}. C) S = {0, 1, 2, 3, ….}. D) S = {0, 1, 2, 3, …, 11, 12}.

88) The table below shows results of a sample of 200 credit card holders whose balances are tabulated against the type of credit card. Among mastercard holders, what is the probability?

Nothing owed Under $1,000 owed Owe $1,000 or more Col Total

Version 1

AmEx

Mastercard

Visa

Row Total

10 6 4 20

6 9 15 30

24 45 81 150

40 60 100 200

A) .5000 B) .1500 C) .0750 D) .2000 E) .0300

89) The table below shows results of a sample of 200 credit card holders whose balances are tabulated against the type of credit card. What is the probability that the card holder holds a Visa card and owes $1,000 or more?

Nothing owed Under $1,000 owed Owe $1,000 or more Col Total

AmEx

Mastercard

Visa

Row Total

10 6 4 20

6 9 15 30

24 45 81 150

40 60 100 200

A) .5000 B) .7500 C) .5400 D) .8100 E) .4050

90) The table below shows results of a sample of 200 credit card holders whose balances are tabulated against the type of credit card. What is the probability that a card holder owes nothing or has a Mastercard?

Nothing owed Under $1,000 owed Owe $1,000 or more Col Total

Version 1

AmEx

Mastercard

Visa

Row Total

10 6 4 20

6 9 15 30

24 45 81 150

40 60 100 200

A) .3200 B) .1500 C) .0300 D) .7000 E) .2000

91)

A sample space is the set of all possible outcomes in an experiment. ⊚ ⊚

92)

The sum of all the probabilities of simple events in a sample space equals one. ⊚ ⊚

93)

true false

Probability is the measure of the relative likelihood that an event will occur. ⊚ ⊚

95)

true false

The sum of the probabilities of all compound events in a sample space equals one. ⊚ ⊚

94)

true false

The probability of the union of two events P( A or B) can exceed one. ⊚ ⊚

Version 1

true false

96)

The empirical view of probability is based on relative frequencies. ⊚ ⊚

true false

97) Grandma’s predicting rain based on how much her arthritis is acting up is an example of the classical view of probability. ⊚ ⊚

true false

98) The odds against an event can be calculated by dividing the event’s probability by the probability of its complement. ⊚ ⊚

true false

99) The union of two events A and B is the event consisting of all outcomes in the sample space that are contained in both event A and event B. ⊚ ⊚

100)

The general law of addition for probabilities says P( A or B) = P( A) + P( B) − P( A ∩ B). ⊚ ⊚

101)

true false

Events A and B are mutually exclusive if P( A ∩ B) = 0.

Version 1

⊚ ⊚

102)

Independent events are mutually exclusive. ⊚ ⊚

103)

true false

If events A and B are dependent, it can be concluded that one event causes the other. ⊚ ⊚

107)

true false

Two events A and B are independent if P( A | B) is the same as P( A). ⊚ ⊚

106)

true false

P( A | B) is the joint probability of events A and B divided by the probability of A. ⊚ ⊚

105)

true false

If events A and B are mutually exclusive, then P( A) + P( B) = 0. ⊚ ⊚

104)

true false

For any event A, the probability of A is always 0 ≤ P( A) ≤ 1.

Version 1

⊚ ⊚

108)

true false

If events A and B are mutually exclusive, the joint probability of the events is zero. ⊚ ⊚

true false

109) When the outcome of a random experiment is a continuous measurement, the sample space is cannot be discrete. ⊚ ⊚

110)

If A and B are independent events, then P( A or B) = P( A) P( B). ⊚ ⊚

111)

true false

The probability of A and its complement ( A´) will always sum to one. ⊚ ⊚

113)

true false

If A and B are mutually exclusive events, then P( A ∩ B) = P( A) + P( B). ⊚ ⊚

112)

true false

If event A occurs, then its complement ( A´) will also occur.

Version 1

⊚ ⊚

114)

The sum of the probabilities of two mutually exclusive events is one. ⊚ ⊚

115)

true false

The general law of addition for probabilities says P( A or B) = P( A) P( B). ⊚ ⊚

117)

true false

P( A ∩ B) = .50 is an example of a joint probability. ⊚ ⊚

116)

true false

If P( A) = .50, P( B) = .30, and P( A ∩ B) = .15, then A and B are independent events. ⊚ ⊚

true false

118) Insurance company life tables are an example of the classical ( a priori) approach to probability. ⊚ ⊚

119)

true false

When two events cannot occur at the same time, they are said to be mutually exclusive.

Version 1

⊚ ⊚

120)

true false

The probability of events A or B occurring can be found by summing their probabilities. ⊚ ⊚

true false

121) When two events A and B are independent, the probability of their intersection can be found by multiplying their probabilities. ⊚ ⊚

122)

true false

Two events are mutually exclusive when they contain no outcomes in common. ⊚ ⊚

true false

123) In a contingency table, the probability of the union of two events is found by taking the frequency of the intersection of the two events and dividing by the total. ⊚ ⊚

true false

124) Bayes’ Theorem shows how to revise a prior probability to obtain a conditional or posterior probability when another event’s occurrence is known. ⊚ ⊚

Version 1

true false

125) The union of two events is all outcomes in either or both, while the intersection is only those events in both. ⊚ ⊚

126)

true false

A contingency table is a cross-tabulation of frequencies for two categorical variables. ⊚ ⊚

true false

127) The number of arrangements of sampled items drawn from a population is found with the formula for permutations (if order is important) or combinations (if order does not matter). ⊚ ⊚

128)

If P( A) = .20 then the odds against event A’s occurrence are 4 to 1. ⊚ ⊚

129)

true false

The value of 7! is 5040. ⊚ ⊚

true false

130) A marginal probability is found by dividing a row total by the column total in a contingency table.

Version 1

⊚ ⊚

true false

131) A conditional probability is found by dividing the intersection frequency by either the associated row total or column total in a contingency table. ⊚ ⊚

true false

132) A joint probability is found by dividing the intersection frequency by the total sample size in a contingency table. ⊚ ⊚

133)

The number of combinations of 7 things taking 3 at a time is 35. ⊚ ⊚

134)

true false

The number of permutations of 7 things taking 3 at a time is 35. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 05_7e_Doane 1) A 2) A 3) C 4) B 5) C 6) C 7) A 8) C 9) A 10) C 11) C 12) A 13) C 14) A 15) C 16) B 17) D 18) A 19) A 20) C 21) C 22) D 23) B 24) C 25) A 26) D Version 1

27) B 28) C 29) D 30) C 31) A 32) D 33) A 34) C 35) B 36) C 37) B 38) C 39) A 40) C 41) C 42) C 43) B 44) C 45) A 46) C 47) C 48) C 49) D 50) D 51) B 52) A 53) C 54) D 55) D 56) D Version 1

57) B 58) C 59) C 60) D 61) C 62) A 63) B 64) C 65) B 66) B 67) C 68) B 69) C 70) A 71) D 72) B 73) A 74) A 75) B 76) A 77) C 78) B 79) D 80) B 81) A 82) A 83) A 84) C 85) B 86) A Version 1

87) D 88) D 89) E 90) A 91) TRUE 92) TRUE 93) FALSE 94) TRUE 95) FALSE 96) TRUE 97) FALSE 98) FALSE 99) FALSE 100) TRUE 101) TRUE 102) FALSE 103) FALSE 104) FALSE 105) TRUE 106) FALSE 107) TRUE 108) TRUE 109) TRUE 110) FALSE 111) FALSE 112) TRUE 113) FALSE 114) FALSE 115) TRUE 116) FALSE Version 1

117) TRUE 118) FALSE 119) TRUE 120) FALSE 121) TRUE 122) TRUE 123) FALSE 124) TRUE 125) TRUE 126) TRUE 127) TRUE 128) TRUE 129) TRUE 130) FALSE 131) TRUE 132) TRUE 133) TRUE 134) FALSE

Version 1

CHAPTER 6 1)

A discrete probability distribution

A) is a listing of all possible values of the random variable. B) assigns a probability to each possible value of the random variable. C) can assume values between −1 and +1. D) is independent of the parameters of the distribution.

Which of the following isnot true about a discrete probability distribution

A) A PDF lists all values ofX and the associated probabilities. B) A CDF lists all values ofX and the cumulative probability for each X value. C) A discrete probability distribution can have probabilities that sum to more than 1. D) A discrete probability distribution can have probabilities that are between 0 and 1.

The number of male babies in a sample of 10 randomly chosen babies is a

A) continuous random variable. B) poisson random variable. C) binary random variable. D) binomial random variable.

4) Define a discrete random variable to be the number of evenings that restaurant is fully booked with reservations out of a 30-day month. Which of the following binomial distribution characteristics is most likelynot true?

Version 1

A) Each evening is a trial with two outcomes: fully booked or not fully booked. B) Evenings can be assumed to be independent trials. C) Each evening has the same probability of being fully booked. D) The number of trails is fixed.

A discrete random variable

A) can be treated as continuous when it has a large range of values. B) cannot be treated as continuous even when it has a large range of values. C) is best avoided if at all possible when it has a large range of values. D) is usually uniformly distributed when it has a large range of values.

Which is not a discrete random variable?

A) The number of defects in a 4 × 8 sheet of plywood. B) The number of female passengers who board a plane. C) The time until failure of a vehicle headlamp. D) The number of correct answers on a statistics exam.

Which is a not a discrete random variable?

A) The number of births in a hospital on a given day. B) The number of fives obtained in four rolls of a die. C) The hourly earnings of a call center employee in Boston. D) The number of applicants applying for a civil service job.

Which statement is incorrect?

Version 1

A) The Poisson distribution is always skewed right. B) The binomial distribution may be skewed left or right. C) The discrete uniform distribution is always symmetric. D) The hypergeometric distribution is always symmetric.

9) The random variable X is the number of shots it takes before you make the first free throw in basketball. Assuming the probability of success (making a free throw) is constant from trial to trial, what type of distribution does X follow?

A) binomial B) poisson C) hypergeometric D) geometric

10) Which probability model is the most appropriate to describe the number of burned-out fluorescent tubes in a classroom with 12 fluorescent tubes, assuming a constant probability of a burned-out tube? Assume the bulbs fail independently of one another.

A) binomial B) poisson C) hypergeometric D) geometric

11) Which distribution is most nearly appropriate to describe the number of fatalities in Texas in a given year due to poisonous snakebites?

Version 1

A) binomial B) poisson C) hypergeometric D) geometric

12) Which model is the most appropriate to describe the probability that a call-center operator will make the first sale on the third call, assuming a constant probability of making a sale?

A) binomial B) poisson C) hypergeometric D) geometric

13) In a randomly chosen week, which probability model would you use to describe the number of accidents at the intersection of two streets?

A) binomial B) poisson C) hypergeometric D) geometric

14) Which model best describes the number of nonworking web URLs ("This page cannot be displayed") you encounter in a randomly chosen minute while surfing websites for vacation rental condos?

Version 1

A) binomial B) poisson C) hypergeometric D) geometric

15) Which probability model would you use to describe the number of damaged printers in a random sample of 4 printers taken from a shipment of 28 printers that contains 3 damaged printers?

A) poisson B) hypergeometric C) binomial D) uniform

16) Which model best describes the number of incorrect fare quotations by a well-trained airline ticket agent between 2 p.m. and 3 p.m. on a particular Thursday.

A) binomial B) poisson C) hypergeometric D) geometric

17)

Which model best describes the number of blemishes per sheet of white bond paper?

A) binomial B) poisson C) hypergeometric D) geometric

Version 1

18) To ensure quality, customer calls for airline fare quotations are monitored at random. On a particular Thursday afternoon, ticket agent Bob gives 40 fare quotations, of which 4 are incorrect. In a random sample of 8 of these customer calls, which model best describes the number of incorrect quotations Bob will make?

A) binomial B) poisson C) hypergeometric D) geometric

19) The number of people injured in rafting expeditions on the Colorado River on a randomly chosen Thursday in August is best described by which model?

A) binomial B) poisson C) hypergeometric D) geometric

20) On a particular Thursday in August, 40 Grand Canyon tourists enter a drawing for a free mule ride. Ten of the entrants are European tourists. Five entrants are selected at random to get the free mule ride. Which model best describes the number of European tourists in the random sample?

A) binomial B) poisson C) hypergeometric D) geometric

Version 1

21) Which model best describes the number of births in a hospital until the first twins are delivered?

A) binomial B) poisson C) hypergeometric D) geometric

22) On a randomly chosen Wednesday, which probability model would you use to describe the number of convenience store robberies in Los Angeles?

A) binomial B) poisson C) hypergeometric D) geometric

23) Which probability model would you use to describe the number of customers served at a certain California Pizza Kitchen until the first customer orders split pea soup?

A) binomial B) geometric C) uniform D) poisson

24)

Which distribution has a mean of 5?

Version 1

A) poisson with λ = 25 B) binomial with n = 200, π = .05 C) hypergeometric with N = 100, n = 10, s = 50 D) bernoulli withπ = .3

25)

Of the following, the one that most resembles a Poisson random variable is the number of

A) heads in 200 flips of a fair coin. B) annual power failures at your residence. C) face cards in a bridge hand of 13 cards. D) defective CDs in a spool containing 15 CDs.

26) Assume 30 percent of the population has a nut allergy. Which of the following distributions is most appropriate to describe the number of people in a sample of 42 who have a nut allergy?

A) binomial B) poisson C) uniform D) geometric

27) Assume 30 percent of the population has a nut allergy. Which of the following distributions is most appropriate to describe the number of people eating in a specific restaurant on Friday evening who have a nut allergy?

A) binomial B) poisson C) uniform D) geometric

Version 1

28) A charity raffle prize is $1,000. The charity sells 4,000 raffle tickets. One winner will be selected at random. At what ticket price would a ticket buyer expect to break even?

A) $0.50 B) $0.25 C) $0.75 D) $1.00

29) A die is rolled. If it rolls a 1, 2, or 3, you win $2. If it rolls to a 4, 5, or 6, you lose $1. Calculate the expected winnings.

A) $0.50 B) $3.00 C) $1.50 D) $1.00

30) A fair die is rolled. If it comes up 1 or 2 you win $2. If it comes up 3, 4, 5, or 6, you lose $1. Calculate the expected winnings.

A) $0.00 B) $1.00 C) $0.50 D) $0.25

31) A nonprofit charity carnival has a game of chance: a fair coin is tossed. If it lands heads you win $1.00, and if it lands tails you lose $0.50. How much should a ticket to play this game cost if the carnival wants to break even?

Version 1

A) $0.25 B) $0.50 C) $0.75 D) $1.00

32) Ephemeral Services Corporation (ESCO) knows that nine other companies besides ESCO are bidding for a $900,000 government contract. Each company has an equal chance of being awarded the contract. If ESCO has already spent $100,000 in developing its bidding proposal, what is its expected net profit?

A) $100,000 B) $90,000 C) −$10,000 D) $0

33) The discrete random variable X is the number of students that show up for Professor Smith’s office hours on Monday afternoons. The table below shows the probability distribution for X. What is the expected value E( X) for this distribution? X P(X)

0 .40

1 .30

2 .20

3 .10

Total 1.00

A) 1.2 B) 1.0 C) 1.5 D) 2.0

34) The discrete random variable X is the number of students that show up for Professor Smith’s office hours on Monday afternoons. The table below shows the probability distribution for X. What is the probability that at least 1 student comes to office hours on any given Monday?

Version 1

X P(X)

0 .40

1 .30

2 .20

3 .10

Total 1.00

A) .30 B) .40 C) .50 D) .60

35) The discrete random variable X is the number of students that show up for Professor Smith’s office hours on Monday afternoons. The table below shows the probability distribution for X. What is the probability that fewer than 2 students come to office hours on any given Monday? X P(X)

0 .40

1 .30

2 .20

3 .10

Total 1.00

A) .10 B) .40 C) .70 D) .90

36) The discrete random variable X is the number of passengers waiting at a bus stop. The table below shows the probability distribution for X. What is the expected value E( X) for this distribution? X P(X)

0 .40

1 .30

2 .20

3 .10

Total 1.00

A) 1.1 B) 1.0 C) 1.7 D) 1.9

Version 1

37) Given the following probability distribution, what is the expected value of the random variable X? X 100 150 200 250 300 Sum

P(X) .10 .20 .30 .30 .10 1.00

A) 175 B) 150 C) 200 D) 205

38) Given the following probability distribution with E(X) = 200, what is the variance of the random variable X? X 100 200 300

P(X) .10 .80 .10

A) 200 B) 200,000 C) 2000 D) 4000

39) Given the following probability distribution with E(X) = 200, what is the variance of the random variable X? X

Version 1

P(X)

100 300 500

.70 .10 .20

A) 2600 B) 260,000 C) 260 D) 26,000

40)

Which of the following characterizes a Bernoulli process?

A) a random experiment that has only two outcomes B) the probability of "success" varies with each trial C) either outcome must have the same chance of occurrence D) the “success” must be a desirable outcome

41)

The binomial distribution describes the number of

A) trials to obtain the first "success" in a Bernoulli process. B) trials to obtain n "successes" in a Bernoulli process. C) "successes" or "failures" in a Bernoulli process. D) "successes" in n Bernoulli trials.

42)

Which of the following is not a requirement of a binomial distribution?

A) constant probability of success B) only two possible Bernoulli outcomes C) fixed number of trials D) equally likely outcomes

Version 1

43)

The binomial distribution is symmetrical when

A) π = 1 and 1 − π = 0. B) π = ¼ and 1 − π = ¾. C) π = ½ and 1 − π = ½. D) π = 0 and 1 − π = 1.

44)

The variance will reach a maximum in a binomial distribution when

A) π = 1 and 1 − π = 0. B) π = ¼ and 1 − π = ¾. C) π = ½ and 1 − π = ½. D) π = 0 and 1 − π = 1.

45)

For a sample size(n) of 50, which distribution is most strongly right-skewed?

A) binomial with π = .70 B) binomial with π = .90 C) binomial with π = .40 D) binomial with π = .10

46) A random variable is binomially distributed with n = 16 and π = .40. The expected value and standard deviation of the variables are

Version 1

A) 2.00 and 1.24. B) 4.80 and 4.00. C) 6.40 and 1.96. D) 2.00 and 1.20.

47) The expected value (mean) of a binomial variable is 15. The number of trials is 20. The probability of "success" is

A) .25. B) .50. C) .75. D) .30.

48) If 90 percent of automobiles in Orange County have both headlights working, what is the probability that in a sample of eight automobiles, at least seven will have both headlights working?

A) .6174 B) .3826 C) .8131 D) .1869

49) In Quebec, 90 percent of the population subscribes to the Roman Catholic religion. In a random sample of eight Quebecois, find the probability that the sample contains at least five Roman Catholics.

Version 1

A) .0050 B) .0331 C) .9950 D) .9619

50) Hardluck Harry has a batting average of .200 (i.e., a 20 percent chance of a hit each time he's at bat). Scouts for a rival baseball club secretly observe Harry's performance in 12 random times at bat. What is the probability that Harry will get more than 2 hits?

A) .2055 B) .2362 C) .7946 D) .4417

51) The probability that a visitor to an animal shelter will adopt a dog is .20. Out of nine visits, what is the probability that at least one dog will be adopted?

A) .8658 B) .3020 C) .5639 D) .1342

52) Based on experience, 60 percent of the women who request a pregnancy test at a certain clinic are actually pregnant. In a random sample of 12 women, what is the probability that at least 10 are pregnant?

Version 1

A) .0639 B) .1424 C) .0196 D) .0834

53) If 5 percent of automobiles in Oakland County have one burned-out headlight, what is the probability that, in a sample of 10 automobiles, none will have a burned-out headlight?

A) .5987 B) .3151 C) .0116 D) .1872

54) Jankord Jewelers permits the return of their diamond wedding rings, provided the return occurs within two weeks. Typically, 10 percent are returned. If eight rings are sold today, what is the probability that fewer than three will be returned?

A) .9950 B) .9619 C) .0331 D) .1488

55) The probability that an Oxnard University student is carrying a backpack is .70. If 10 students are observed at random, what is the probability that fewer than 7 will be carrying backpacks?

Version 1

A) .3504 B) .2001 C) .6177 D) .2668

56) An insurance company is issuing 16 car insurance policies. Suppose the probability for a claim during a year is 15 percent. If the binomial probability distribution is applicable, then the probability that there will be at least two claims during the year is equal to

A) .5615. B) .2775. C) .7161. D) .0388.

57) A random variable X is distributed binomially with n = 8 and π = .70. The standard deviation of the variable X is approximately

A) 0.458. B) 2.828. C) 1.680. D) 1.296.

58) Suppose X is binomially distributed with n = 12 and π = .20. The probability that X will be less than or equal to 3 is

A) .5584. B) .7946. C) .2362. D) .7638.

Version 1

59) Which Excel function would generate a single random X value for a binomial random variable with parameters n = 16 and π = .25?

A) =BINOM.DIST(RAND(),16,.25,0) B) =BINOM.DIST(0,16,.25,RAND()) C) =BINOM.INV(16,.25,RAND()) D) =BINOM.INV(0,16,.25,RAND())

60) A network has three independent file servers, each with 90 percent reliability. The probability that the network will be functioning correctly (at least one server is working) at a given time is

A) 99.9 percent. B) 97.2 percent. C) 95.9 percent. D) 72.9 percent.

61)

Which statement concerning the binomial distribution is correct?

A) Its PDF covers all integer values of X from 0 to n. B) Its PDF is the same as its CDF when π = .50. C) Its CDF shows the probability of each value of X. D) Its CDF is skewed right when π < .50.

62) Historically, 2 percent of the stray dogs in Southfield are unlicensed. On a randomly chosen day, the Southfield city animal control officer picks up seven stray dogs. What is the probability that fewer than two will be unlicensed?

Version 1

A) .8681 B) .9921 C) .3670 D) .0076

63)

The domain of X in a Poisson probability distribution is discrete and can include

A) any real X value. B) any integer X value. C) any nonnegative integer X value. D) any X value except zero.

64) On Saturday morning, calls arrive at TicketMaster at a rate of 108 calls per hour. What is the probability of fewer than three calls in a randomly chosen minute?

A) .1607 B) .8913 C) .2678 D) .7306

65) On average, a major earthquake (Richter scale 6.0 or above) occurs three times a decade in a certain California county. Find the probability that at least one major earthquake will occur within the next decade.

A) .7408 B) .1992 C) .1494 D) .9502

Version 1

66) On average, an IRS auditor discovers 4.7 fraudulent income tax returns per day. On a randomly chosen day, what is the probability that she discovers fewer than two?

A) .0518 B) .0427 C) .1005 D) .1523

67) On a Sunday in April, dog bite victims arrive at Carver Memorial Hospital at a historical rate of 0.6 victim per day. On a given Sunday in April, what is the probability that exactly two dog bite victims will arrive?

A) .0875 B) .0902 C) .0988 D) .0919

68) If tubing averages 16 defects per 100 meters, what is the probability of finding exactly 2 defects in a randomly chosen 10-meter piece of tubing?

A) .8795 B) .2674 C) .3422 D) .2584

69) Cars are arriving at a toll booth at a rate of four per minute. What is the probability that exactly eight cars will arrive in the next two minutes?

Version 1

A) .0349 B) .1396 C) .9666 D) .0005

70) if

Arrival of cars per minute at a toll booth may be characterized by the Poisson distribution

A) the arrivals are independent. B) no more than one arrival can occur in a minute. C) there is only one lane leading to the booth. D) the mean arrival rate is at least 30.

71)

The coefficient of variation for a Poisson distribution with λ = 5 is

A) 35.2 percent. B) 58.9 percent. C) 44.7 percent. D) 31.1 percent.

72)

The coefficient of variation for a Poisson distribution with λ = 4 is

A) 35.2 percent. B) 58.9 percent. C) 50.0 percent. D) 26.4 percent.

Version 1

73)

For which binomial distribution would a Poisson approximation be unacceptable?

A) n = 30, π = .02 B) n = 50, π = .03 C) n = 200, π = .10 D) n = 500, π = .01

74)

For which binomial distribution would a Poisson approximation be acceptable?

A) n = 60, π = .08 B) n = 100, π = .15 C) n = 40, π = .03 D) n = 20, π = .20

75)

For which binomial distribution would a Poisson approximation not be acceptable?

A) n = 35, π = .07 B) n = 95, π = .01 C) n = 80, π = .02 D) n = 50, π = .03

76) The true proportion of accounts receivable with some kind of error is .02 for Venal Enterprises. If an auditor randomly samples 200 accounts receivable, what is the approximate Poisson probability that fewer than two will contain errors?

Version 1

A) .1038 B) .0916 C) .1465 D) .0015

77) The probability that a rental car will be stolen is .0004. If 3500 cars are rented, what is the approximate Poisson probability that 2 or fewer will be stolen?

A) .3452 B) .2417 C) .5918 D) .8335

78) The probability that a customer will use a stolen credit card to make a purchase at a certain Target store is .003. If 400 purchases are made in a given day, what is the approximate Poisson probability that 4 or fewer will be with stolen cards?

A) .9053 B) .0076 C) .9923 D) .0555

79) The probability that a ticket holder will miss a flight is .005. If 180 passengers take the flight, what is the approximate Poisson probability that at least 2 will miss the flight?

A) .9372 B) .0628 C) .1647 D) .2275

Version 1

80) The probability that a certain daily flight’s departure from ORD to LAX is delayed is .02. Over six months, this flight departs 180 times. What is the approximate Poisson probability that it will be delayed fewer than 2 times?

A) .4471 B) .3028 C) .1257 D) .1771

81)

If X is a discrete uniform random variable ranging from 0 to 12, find P( X ≥ 10).

A) .1126 B) .1666 C) .2308 D) .2500

82)

If X is a discrete uniform random variable ranging from one to eight, find P( X < 6).

A) .6250 B) .5000 C) .7500 D) .3750

83)

If X is a discrete uniform random variable ranging from one to eight, what is its mean?

Version 1

A) 4.0 B) 4.5 C) 5.0 D) 5.5

84)

If X is a discrete uniform random variable ranging from 12 to 24, what is its mean?

A) 18.5 B) 16.0 C) 18.0 D) 19.5

85) At Ersatz University, the graduating class of 480 includes 96 guest students from Latvia. A sample of 10 students is selected at random to attend a dinner with the Board of Governors. Use the binomial model to obtain the approximate hypergeometric probability that the sample contains at least three Latvian students.

A) .3222 B) .1209 C) .8791 D) .6778

86) There are 90 passengers on a commuter flight from SFO to LAX, of whom 27 are traveling on business. In a random sample of five passengers, use the binomial model to find the approximate hypergeometric probability that there is at least one business passenger.

Version 1

A) .3087 B) .1681 C) .3602 D) .8319

87) Use the binomial model to find the approximate hypergeometric probability of at least two damaged flash drives in a sample of five taken from a shipment of 150 that contains 30 damaged flash drives.

A) .9421 B) .0579 C) .7373 D) .2627

88) On a particular day, 112 of 280 passengers on a particular DTW-LAX flight used the eticket check-in kiosk to obtain boarding passes. In a random sample of eight passengers, use the binomial model to find the approximate hypergeometric probability that four will have used the e-ticket check-in kiosk to obtain boarding passes.

A) .2322 B) .8263 C) .2926 D) .5613

89) A clinic employs nine physicians. Five of the physicians are female. Four patients arrive at once. Assuming the doctors are assigned randomly to patients, what is the probability that all of the assigned physicians are female?

Version 1

A) .0397 B) .0295 C) .0808 D) .0533

90) There is a .02 probability that a customer’s Visa charge will be rejected at a certain Target store because the transaction exceeds the customer’s credit limit. What is the probability that the first such rejection occurs on the third Visa transaction?

A) .0192 B) .0025 C) .0247 D) .0200

91) Ten percent of the corporate managers at Axolotl Industries majored in humanities. If you start interviewing Axolotl managers, what is the probability that the first humanities major is the fifth manager that you interview?

A) .0656 B) .8561 C) .5904 D) .4095

92) Ten percent of the corporate managers at Axolotl Industries majored in humanities. What is the expected number of managers to be interviewed before finding the first one with a humanities major?

Version 1

A) 15 B) 20 C) 10 D) 17

93) When you send out a resume, the probability of being called for an interview is .20. What is the probability that the first interview occurs on the fourth resume that you send out?

A) .4096 B) .1024 C) .2410 D) .0016

94) When you send out a resume, the probability of being called for an interview is .20. What is the expected number of resumes you send out before you get the first interview?

A) 5 B) 7 C) 10 D) 12

95) When you send out a resume, the probability of being called for an interview is .20. What is the probability that you get your first interview within the first five resumes that you send out?

A) .6723 B) .1024 C) .2410 D) .0016

Version 1

96) There is a .02 probability that a customer’s Visa charge will be rejected at a certain Target store because the transaction exceeds the customer’s credit limit. What is the probability that the first such rejection occurs within the first 20 Visa transactions?

A) .1362 B) .4000 C) .3324 D) .4538

97) There is a .02 probability that a customer’s Visa charge will be rejected at a certain Target store because the transaction exceeds the customer’s credit limit. What is the expected number of Visa transactions until the first one is rejected?

A) 10 B) 20 C) 50 D) 98

98)

The geometric distribution best describes

A) the number of successes in a sample of n trials. B) the number of trials until the first success. C) the number of events in a given unit of time. D) the process of sampling without replacement.

99)

The CDF for the geometric distribution shows

Version 1

A) the probability of success in a random experiment consisting of n independent trials. B) the probability that the first success will occur within a given number of trials. C) the probability that no success will be obtained in a given Bernoulli trial. D) the probability of more than one success in the first n trials.

100) If the probability of success is .25, what is the probability of obtaining the first success within the first three trials?

A) .4218 B) .5781 C) .1406 D) .2228

101) If the probability of success is .30, what is the probability of obtaining the first success within the first five trials?

A) .0024 B) .8319 C) .1681 D) .9976

102) A project has three independent stages that must be completed in sequence. The time to complete each stage is a random variable. The expected times to complete the stages are μ1 = 23, μ2 = 11, μ3 = 17. The expected project completion time is

A) 51. B) 23. C) 40. D) 32.

Version 1

103) A project has 3 independent stages that must be completed in sequence. The time to complete each stage is a random variable. The standard deviations of the completion times for the stages are σ1 = 5, σ2 = 4, σ3 = 6. The standard deviation of the overall project completion time is

A) 8.77. B) 15.0. C) 14.2. D) 9.24.

104) A stock portfolio consists of two stocks X and Y. Their daily closing prices are independent random variables with standard deviations σX = 2.51 and σY = 5.22. What is the standard deviation of the sum of the closing prices of these two stocks?

A) 33.55 B) 6.48 C) 7.73 D) 5.79

105) A stock portfolio consists of two stocks X and Y. Their daily closing prices are correlated random variables with variances σX2 = 3.51 and σY2= 5.22, and covariance σXY = −1.55. What is the standard deviation of the sum of the closing prices of these two stocks?

A) 5.63 B) 7.18 C) 8.73 D) 2.68

Version 1

106) The expected value of a random variable X is 140 and the standard deviation is 14. The standard deviation of the random variable Y = 3 X − 10 is

A) 42. B) 6.48. C) 14. D) 32.

107) The expected value of a random variable X is 10 and the standard deviation is 2. The standard deviation of the random variable Y = 2 X − 10 is

A) 2. B) 4. C) −10. D) −6.

108) A random variable is a function or rule that assigns a numerical value to each outcome in the sample space of a stochastic (chance) experiment. ⊚ ⊚

109)

A discrete random variable has a countable number of distinct values. ⊚ ⊚

110)

true false

A discrete random variable must have a clear upper limit. ⊚ ⊚

Version 1

true false 33

111)

A discrete random variable value can have two distinct probability values. ⊚ ⊚

112)

true false

CDF values will increase as X values increase. ⊚ true ⊚ false

113) The expected value of a discrete random variable E( X) is the sum of all X values multiplied by their respective probabilities ⊚ ⊚

true false

114) A discrete distribution can be described by its probability density function (PDF) or by its cumulative distribution function (CDF). ⊚ ⊚

115)

A random variable may be discrete or continuous, but not both. ⊚ ⊚

116)

true false

The expected value of a discrete random variableE(X) must be an observableX value.

Version 1

⊚ ⊚

true false

117) To describe the number of blemishes per sheet of white bond paper, we would use a discrete uniform distribution. ⊚ ⊚

true false

118) The outcome of the role of a singe dice can be described as a discrete uniform distribution. ⊚ true ⊚ false

119)

A discrete binomial distribution is skewed right when π > .50. ⊚ ⊚

120)

When π = .70 the discrete binomial distribution is negatively skewed. ⊚ ⊚

121)

true false

Each trial in a binomial distribution must have the same probability of success. ⊚ ⊚

Version 1

true false

122) The Poisson distribution describes the number of occurrences within a randomly chosen unit of time or space. ⊚ ⊚

123)

true false

The Poisson distribution can be skewed either left or right, depending on λ. ⊚ ⊚

true false

124) Although the shape of the Poisson distribution is positively skewed, it becomes more nearly symmetric as its mean becomes larger. ⊚ ⊚

true false

125) As a rule of thumb, the Poisson distribution can be used to approximate a binomial distribution when n ≥ 20 and π ≤ .05. ⊚ ⊚

126)

true false

The hypergeometric distribution is skewed right. ⊚ ⊚

true false

127) The hypergeometric distribution assumes that the probability of a success remains the same from one trial to the next.

Version 1

⊚ ⊚

128)

true false

The hypergeometric distribution is not applicable if sampling is done with replacement. ⊚ ⊚

true false

129) As a rule of thumb, the binomial distribution can be used to approximate the hypergeometric distribution whenever the population is at least 20 times as large as the sample. ⊚ ⊚

true false

130) An example of a geometric random variable is the number of pine trees with pine beetle infestation in a random sample of 15 pine trees in Colorado. ⊚ ⊚

true false

131) Calculating the probability of getting three aces in a hand of five cards dealt from a deck of 52 cards would require the use of a hypergeometric distribution. ⊚ ⊚

true false

132) The Poisson distribution is appropriate to describe the number of babies born in a small hospital on a given day. ⊚ ⊚

Version 1

true false

133)

The gender (M,F) of a randomly chosen unborn child is a Bernoulli event. ⊚ ⊚

134)

The Poisson distribution has only one parameter. ⊚ ⊚

135)

true false

The two outcomes (success, failure) in the Bernoulli model are equally likely. ⊚ ⊚

138)

true false

Customer arrivals per unit of time would tend to follow a binomial distribution. ⊚ ⊚

137)

true false

The standard deviation of a Poisson random variable is the square root of its mean. ⊚ ⊚

136)

true false

The expected value of a random variable is its mean. ⊚ ⊚

Version 1

true false

Version 1

Answer Key Test name: Chap 06_7e_Doane 1) B 2) C 3) D 4) C 5) A 6) C 7) C 8) D 9) D 10) A 11) B 12) D 13) B 14) B 15) B 16) B 17) B 18) C 19) B 20) C 21) D 22) B 23) B 24) C 25) B 26) A Version 1

27) B 28) B 29) A 30) A 31) A 32) D 33) B 34) D 35) C 36) B 37) D 38) C 39) D 40) A 41) D 42) D 43) C 44) C 45) D 46) C 47) C 48) C 49) C 50) D 51) A 52) D 53) A 54) B 55) A 56) C Version 1

57) D 58) B 59) C 60) A 61) A 62) B 63) C 64) D 65) D 66) A 67) C 68) D 69) B 70) A 71) C 72) C 73) C 74) C 75) A 76) B 77) D 78) C 79) D 80) C 81) C 82) A 83) B 84) C 85) A 86) D Version 1

87) D 88) A 89) A 90) A 91) A 92) C 93) B 94) A 95) A 96) C 97) C 98) B 99) B 100) B 101) B 102) A 103) A 104) D 105) D 106) A 107) B 108) TRUE 109) TRUE 110) FALSE 111) FALSE 112) TRUE 113) TRUE 114) TRUE 115) TRUE 116) FALSE Version 1

117) FALSE 118) TRUE 119) FALSE 120) TRUE 121) TRUE 122) TRUE 123) FALSE 124) TRUE 125) TRUE 126) FALSE 127) FALSE 128) TRUE 129) TRUE 130) FALSE 131) TRUE 132) TRUE 133) TRUE 134) TRUE 135) TRUE 136) FALSE 137) FALSE 138) TRUE

Version 1

CHAPTER 7 1) A machine dispenses water into a glass. Assuming that the amount of water dispensed follows a continuous uniform distribution from 10 ounces to 16 ounces, the average amount of water dispensed by the machine is

A) 12 ounces. B) 13 ounces. C) 14 ounces. D) 16 ounces.

2) A machine dispenses water into a glass. Assuming that the amount of water dispensed follows a continuous uniform distribution from 10 ounces to 16 ounces, the standard deviation of the amount of water dispensed is about

A) 1.73 ounces. B) 3.00 ounces. C) 0.57 ounce. D) 3.51 ounces.

3) A machine dispenses water into a glass. Assuming that the amount of water dispensed follows a continuous uniform distribution from 10 ounces to 16 ounces, what is the probability that 13 or more ounces will be dispensed in a given glass?

A) .1666 B) .3333 C) .5000 D) .6666

4) A random variable X is best described by a continuous uniform distribution from 20 to 45 inclusive. The mean of this distribution is Version 1

A) 30.5. B) 31.5. C) 32.5. D) 33.5.

5) A random variable X is best described by a continuous uniform distribution from 20 to 45 inclusive. The standard deviation of this distribution is approximately

A) 52.1. B) 32.5. C) 6.85. D) 7.22.

6) A random variable X is best described by a continuous uniform distribution from 20 to 45 inclusive. What is P(30 ≤ X ≤ 40)?

A) .20 B) .40 C) .60 D) .80

7) The Excel function =800*RAND() would generate random numbers with standard deviation approximately equal to

A) 200. B) 188. C) 231. D) 400.

Version 1

8) The Excel function =40*RAND() would generate random numbers with standard deviation approximately equal to

A) 13.33. B) 20.00. C) 11.55. D) 19.27.

9) If arrivals occur at a mean rate of 3.6 events per hour, the exponential probability of waiting more than 0.5 hour for the next arrival is

A) .2407. B) .1653. C) .1222. D) .5000.

10) If arrivals occur at a mean rate of 3.6 events per hour, the exponential probability of waiting less than 0.5 hour for the next arrival is

A) .7122. B) .8105. C) .8347. D) .7809.

11) If arrivals occur at a mean rate of 2.6 events per minute, the exponential probability of waiting more than 1.5 minutes for the next arrival is

Version 1

A) .0202. B) .0122. C) .0535. D) .2564.

12) If arrivals occur at a mean rate of 1.6 events per minute, the exponential probability of waiting less than 1 minute for the next arrival is

A) .2019. B) .7104. C) .8812. D) .7981.

13) Bob’s z-score for the last exam was 1.52 in Professor Axolotl’s class BIO 417, “Life Cycle of the Ornithorhynchus.” Bob said, “Oh, good, my score is in the top 10 percent.” Assuming a normal distribution of scores, which statement is most correct?

A) Bob’s score is in the top 10 percent of the class. B) Bob scored below the top 10 percent of the class. C) Bob scored in the top 5 percent of the class. D) We must know the sample size to determine where Bob’s score fell with respect to the class.

14) The lengths of brook trout caught in a certain Colorado stream are normally distributed with a mean of 14 inches and a standard deviation of 3 inches. What proportion of brook trout caught will be between 12 and 18 inches in length?

Version 1

A) .6563 B) .6826 C) .2486 D) .4082

15) The lengths of brook trout caught in a certain Colorado stream are normally distributed with a mean of 14 inches and a standard deviation of 3 inches. The first quartile for the lengths of brook trout would be

A) 16.01 inches. B) 11.00 inches. C) 11.98 inches. D) 10.65 inches.

16) The lengths of brook trout caught in a certain Colorado stream are normally distributed with a mean of 14 inches and a standard deviation of 3 inches. What lower limit should the State Game Commission set on length if it is desired that 80 percent of the catch may be kept by fishers?

A) 12.80 inches B) 11.48 inches C) 12.00 inches D) 9.22 inches

17) In Melanie’s Styling Salon, the time to complete a simple haircut is normally distributed with a mean of 25 minutes and a standard deviation of 4 minutes. What percentage of customers require less than 32 minutes for a simple haircut?

Version 1

A) 95.99 percent B) 99.45 percent C) 97.72 percent D) 45.99 percent

18) In Melanie’s Styling Salon, the time to complete a simple haircut is normally distributed with a mean of 25 minutes and a standard deviation of 4 minutes. The slowest quartile of customers will require more than how many minutes for a simple haircut?

A) 3( n + 1)/4 minutes B) 26 minutes C) 25.7 minutes D) 27.7 minutes

19) In Melanie’s Styling Salon, the time to complete a simple haircut is normally distributed with a mean of 25 minutes and a standard deviation of 4 minutes. For a simple haircut, the middle 90 percent of the customers will require

A) between 18.4 and 31.6 minutes. B) between 19.9 and 30.1 minutes. C) between 20.0 and 30.0 minutes. D) between 17.2 and 32.8 minutes.

20) The area under the normal curve between z = 0 and z = 1 is the normal curve between z = 1 and z = 2.

the area under

A) less than. B) greater than. C) equal to.

Version 1

21) The price-earnings ratio for firms in a certain industry follows the normal distribution. In this industry, a firm whose price-earnings ratio has a standardized value of z = 1.00 is approximately in the highest percent of firms in the industry.

A) 16 percent B) 34 percent C) 68 percent D) 75 percent

22) A student’s grade on an examination was transformed to a z value of 0.67. Assuming a normal distribution, we know that she scored approximately in the top

A) 15 percent. B) 50 percent. C) 40 percent. D) 25 percent.

23) The MPG (miles per gallon) for a certain compact car is normally distributed with a mean of 31 and a standard deviation of 0.8. What is the probability that the MPG for a randomly selected compact car would be less than 32? A) .3944 B) .8944 C) .1056 D) .5596

24) The probability is .80 that a standard normal random variable is between − z and + z. The value of z is approximately

Version 1

A) 1.28. B) 1.35. C) 1.96. D) 1.45.

25) The time required for a citizen to complete the 2020 U.S. Census "long" form is normally distributed with a mean of 40 minutes and a standard deviation of 10 minutes. What proportion of the citizens will require less than one hour?

A) .4772 B) .9772 C) .9974 D) .9997

26) The time required for a citizen to complete the 2020 U.S. Census “long” form is normally distributed with a mean of 40 minutes and a standard deviation of 10 minutes. The slowest 10 percent of the citizens would need at least how many minutes to complete the form?

A) 27.2 B) 35.8 C) 52.8 D) 59.6

27) The time required for a citizen to complete the 2020 U.S. Census “long” form is normally distributed with a mean of 40 minutes and a standard deviation of 10 minutes. What is the third quartile (in minutes) for the time required to complete the form?

Version 1

A) 44.75 B) 46.75 C) 47.50 D) 52.50

28) Exam scores were normal in BIO 200. Jason’s exam score was one standard deviation above the mean. What percentile is he in?

A) 68th B) 75th C) 78th D) 84th

29) Compared to the area between z = 1.00 and z = 1.25, the area between z = 2.00 and z = 2.25 in the standard normal distribution will be

A) smaller. B) larger. C) the same. D) impossible to compare without knowing μ and σ.

30) A large number of applicants for admission to graduate study in business are given an aptitude test. Scores are normally distributed with a mean of 460 and standard deviation of 80. What fraction of applicants would you expect to have scores of 600 or above?

A) .0401 B) .4599 C) .5401 D) .0852

Version 1

31) A large number of applicants for admission to graduate study in business are given an aptitude test. Scores are normally distributed with a mean of 460 and standard deviation of 80. What fraction of the applicants would you expect to have a score of 400 or above?

A) .2734 B) .7734 C) .7266 D) .7500

32) A large number of applicants for admission to graduate study in business are given an aptitude test. Scores are normally distributed with a mean of 460 and standard deviation of 80. The top 2.5 percent of the applicants would have a score of at least (choose the nearest integer)

A) 606. B) 617. C) 600. D) 646.

33)

If the random variable Z has a standard normal distribution, then P(1.25 ≤ Z ≤ 2.17) is

A) .0906. B) .9200. C) .4700. D) .3944.

34)

If the random variable Z has a standard normal distribution, then P( Z ≤ −1.37) is

Version 1

A) .9147. B) .4147. C) .5016. D) .0853.

35) Assume that X is normally distributed with a mean μ = $64. Given that P( X ≥ $75) = .2981, we can calculate that the standard deviation of X is approximately

A) $20.76. B) $13.17. C) $5.83. D) $7.05.

36) The standard deviation of a normal random variable X is $20. Given that P( X ≤ $10) = .1841 we can determine that the mean of the distribution is equal to

A) $13. B) $26. C) $20. D) $28.

37) The random variableX is normally distributed with mean of 80 and variance of 36. The 67th percentile of the distribution is

A) 72.00. B) 95.84. C) 90.01. D) 82.64.

Version 1

38)

The area under the normal curve between the 20th and 70th percentiles is

A) .7000. B) .5000. C) .9193.

39)

The variable in a normal distribution can assume any value between

A) −3 and +3. B) −4 and +4. C) −1 and +1. D) −∞ and +∞.

40)

What are the mean and standard deviation for the standard normal distribution?

A) μ = 0, σ = 0 B) μ = 1, σ = 1 C) μ = 1, σ = 0 D) μ = 0, σ = 1

41)

Any two normal curves are the same except for their

A) standard deviations. B) means. C) standard deviations and means. D) standard deviations, means, skewness, and kurtosis.

Version 1

42) Light bulbs are normally distributed with an average lifetime of 1000 hours and a standard deviation of 250 hours. The probability that a light bulb picked at random will last less than 1500 hours is about

A) 97.72 percent. B) 95.44 percent. C) 75.00 percent. D) 68.00 percent.

43)

To convert a normally distributed variable X into a standard Z score we would

A) subtract the mean from the original observation and divide the result by the variance. B) subtract the mean from the original observation and divide the result by the standard deviation. C) add the mean and the original observation, then divide by the variance. D) subtract the mean from the standard deviation and divide by the variance.

44)

Regarding continuous probability distributions, which statement is incorrect?

A) The triangular distribution may be skewed left or right. B) The uniform distribution is never skewed. C) The normal distribution is sometimes skewed. D) The exponential distribution is always skewed right.

45) Which model best describes your waiting time until you get the next nonworking web URL ("This page cannot be displayed") as you click on various websites for Florida condo rentals?

Version 1

A) triangular B) uniform C) normal D) exponential

46) On average, a major earthquake (Richter scale 6.0 or above) occurs 3 times a decade in a certain California county. What is the probability that less than six months will pass before the next earthquake?

A) .1393 B) .8607 C) .0952 D) .9048

47) If the mean time between in-flight aircraft engine shutdowns is 12,500 operating hours, the 90th percentile of waiting times to the next shutdown will be

A) 20,180 hours. B) 28,782 hours. C) 23,733 hours. D) 18,724 hours.

48) On average, 15 minutes elapse between discoveries of fraudulent corporate tax returns in a certain IRS office. What is the probability that less than 30 minutes will elapse before the next fraudulent corporate tax return is discovered?

Version 1

A) .1353 B) .6044 C) .7389 D) .8647

49) If the mean time between unscheduled maintenance of LCD displays in a hospital’s CT scan facility is 4,000 operating hours, what is the probability of unscheduled maintenance in the next 5,000 hours?

A) .8000 B) .7135 C) .2865 D) .5000

50) A certain assembly line at Vexing Manufacturing Company averages 30 minutes between breakdowns. What is the probability that less than 6 minutes will elapse before the next breakdown?

A) .8187 B) .0488 C) .1813 D) .2224

51) A certain assembly line at Vexing Manufacturing Company averages 30 minutes between breakdowns. The median time between breakdowns is

Version 1

A) 30.0 minutes. B) 35.7 minutes. C) 25.4 minutes. D) 20.8 minutes.

52) Which probability model is most appropriate to describe the waiting time (working days) until an office photocopier breaks down (i.e., requires unscheduled maintenance)?

A) normal B) uniform C) exponential D) poisson

53) On the last exam in FIN 417, “Capital Budgeting Strategies” Bob’s z-score was −1.15. Bob said, “Yipe! My score is within the bottom quartile.” Assuming a normal distribution, is Bob right?

A) Yes B) No C) must know the class size to answer

54) Exam scores were normal in MIS 200. Jason’s exam score was 1.41 standard deviations above the mean. What percentile is he in?

A) 68th B) 75th C) 84th D) 92nd

Version 1

55) Compared to the area between z = 0.50 and z = 0.75, the area between z = 1.50 and z = 1.75 in the standard normal distribution will be

A) smaller. B) larger. C) the same.

56) If GMAT scores for applicants at Oxnard Graduate School of Business are N(500, 50), then the top 5 percent of the applicants would have a score of at least (choose the nearest integer)

A) 575. B) 582. C) 601. D) 608.

57)

If the random variable Z has a standard normal distribution, then P(1.17 ≤ Z ≤ 2.26) is

A) .1091. B) .1203. C) .2118. D) .3944.

58)

If the random variable Z has a standard normal distribution, then P( Z ≤ −1.72) is

Version 1

A) .9573. B) .0446. C) .5016. D) .0427.

59) Excel’s =100*RAND() function produces continuous random numbers that are uniformly distributed between 0 and 100. The standard deviation of this distribution is approximately

A) 50.00. B) 28.87. C) 33.33. D) 25.00.

60) Excel’s =RAND() function produces random numbers that are uniformly distributed between 0 and 1. The mean of this distribution is

A) .5000. B) .2500. C) .3333. D) .2887.

61) Excel’s =RAND() function produces random numbers that are uniformly distributed from 0 to 1. What is the probability that the random number exceeds .75?

A) 75 percent B) 50 percent C) 25 percent

Version 1

62) 33)?

Which is the correct Excel formula for the 80th percentile of a distribution that is N(475,

A) =NORM.DIST(80, 475, 33,1) B) =NORM.INV(0.80, 475, 33) C) =NORM.S.INV((80 − 475)/33) D) =NORM.S.DIST(80,475,33,1)

63) If arrivals follow a Poisson distribution with mean 1.2 arrivals per minute, find the 75th percentile of waiting times until the next arrival (i.e., 75 percent below).

A) 1.155 minutes (69.3 seconds) B) 0.240 minute (14.4 seconds) C) 1.919 minutes (115.1 seconds) D) −0.240 minute (−14.4 seconds)

64) A software developer makes 175 phone calls to its current customers. There is an 8 percent chance of reaching a given customer (instead of a busy signal, no answer, or answering machine). The normal approximation of the probability of reaching at least 20 customers is

A) .022. B) .007. C) .063. D) .937.

65) For Gardyloo Manufacturing, the true proportion of accounts receivable with some kind of error is .20. If an auditor randomly samples 225 accounts receivable, what is the approximate normal probability that 39 or fewer will contain errors?

Version 1

A) .1797 B) .2097 C) .1587 D) .0544

66) A letter is mailed to a sample of 500 homeowners. Based on past experience, the probability of an undeliverable letter is 0.06. The normal approximation to the binomial probability of 40 or more undeliverable letters is

A) .9632. B) .0368. C) .2305. D) .7695.

67) In a True-False exam with 100 questions, passing requires a score of at least 60. What is the approximate normal probability that a "guesser" will score at least 60 points?

A) .0287 B) .4713 C) .0251 D) .0377

68) A multiple-choice exam has 100 questions. Each question has five choices. What would be the approximate probability that a "guesser" could achieve a score of 30 or more?

A) .0088 B) .0062 C) .0015 D) .4913

Version 1

69)

For which binomial distribution would a normal approximation be most acceptable?

A) n = 50, π = .05 B) n = 100, π = .04 C) n = 40, π = .25 D) n = 400, π = .02

70) Historically, the default rate on a certain type of commercial loan is 20 percent. If a bank makes 100 of these loans, what is the approximate probability that at least 26 will result in default?

A) .2000 B) .0668 C) .0846 D) .0336

71) A company employs 300 employees. Each year, there is a 30 percent turnover rate for employees. We want to do a normal approximation to the binomial distribution of the number of employees who leave each year. For this normal approximation, the mean is and the standard deviation is .

A) 90; 63 B) 90; 7.937 C) 90; 30 D) 90; 15

72) The probability that a rental car will be stolen is .001. If 25,000 cars are rented from Hertz, what is the normal approximation to the probability that fewer than 20 will be stolen?

Version 1

A) .2577 B) .1335 C) .1128 D) .8335

73) If adult male heights are normally distributed with a mean of 180 centimeter and a standard deviation of 7 centimeter, how high should an aircraft lavatory door be to ensure that 99.9 percent of adult males will not have to stoop as they enter?

A) 195.7 centimeter B) 201.6 centimeter C) 207.3 centimeter D) 201.4 centimeter

74) TotCo is developing a new deluxe baby bassinet. If the length of a newborn baby is normally distributed with a mean of 50 centimeter and a standard deviation of 5 centimeter, what should be the interior length of the bassinet to ensure that 99 percent of newborn babies will fit, with a safety margin of 15 centimeter on each end of the bassinet?

A) 95.45 centimeter B) 85.22 centimeter C) 91.63 centimeter D) 98.92 centimeter

75)

The triangular distribution T(4, 12, 26) has a mean of

Version 1

A) 14. B) 18. C) 12. D) 13.

76)

The triangular distribution T(0, 10, 20) has a standard deviation of

A) 4.082. B) 3.775. C) 3.024. D) 2.994.

77)

The triangular distribution T(5, 23, 62) has a mean of

A) 23. B) 30. C) 33. D) 35.

78)

The triangular distribution T(10, 20, 50) has a standard deviation of

A) 9.498. B) 9.225. C) 8.498. D) 7.710.

79)

Which statement is incorrect?

Version 1

A) The triangular distribution always has a single mode. B) The mean of the triangular distribution is ( a + b + c)/3. C) The triangular distribution is right-skewed. D) The triangular distribution can be skewed left or right.

80) Bob used a triangular distribution of T(20, 30, 61) to represent his daily commute time (minutes). Which statement is incorrect?

A) The distribution is right-skewed. B) The mode of the distribution exceeds the mean. C) The mean of the distribution is 37. D) The midrange of the distribution is 40.5.

81) Phyllis used a triangular distribution of T(10, 15, 20) to represent her daily commute time (minutes). Which statement is incorrect?

A) The distribution is right-skewed. B) The mode of the distribution is at the mean. C) The mean of the distribution is 15. D) The midrange of the distribution is 15.

82)

In a continuous distribution,

A) P( X < 5) is the same as P( X ≤ 5). B) P( X < 5) is less than P( X ≤ 5). C) P( X < 5) is more than P( X ≤ 5). D) One cannot determine the relationship betweenP(X < 5) andP(X ≤ 5).

Version 1

83)

In a continuous distribution the

A) PDF is usually higher than the CDF. B) CDF is used to find left-tail probabilities. C) PDF shows the area under the curve. D) CDF is usually the same as the PDF.

84) If the mean waiting time for the next arrival is 12 minutes, what is the median waiting time?

A) 7.2 minutes B) 8.3 minutes C) 9.1 minutes D) 12 minutes

85) If the mean waiting time for the next arrival is 18 minutes, what is the first quartile (25th percentile) for waiting times?

A) 13 minutes B) 7.9 minutes C) 5.2 minutes D) 3.1 minutes

Version 1

86)

Could this function be a PDF?

A) Yes. B) No. C) It depends on x. D) It depends on how f(x) is defined.

87)

Could this function be a PDF?

Version 1

A) Yes. B) No. C) It depends on x. D) Not possible to determine.

88) The ages of job applicants for a security guard position are uniformly distributed between 25 and 65. How many standard deviations below the mean would a 25-year-old job applicant be?

A) fewer than 2\σ B) more than 3\σ C) impossible to determine from given information D) between 2σ and 3σ"

89)

The figure shows a standard normal N(0,1) distribution. Find the shaded area.

A) .6444 B) .7514 C) .9245 D) .9850

Version 1

90)

The figure shows a standard normal N(0,1) distribution. Find the shaded area.

A) .4400 B) .3300 C) .2998 D) .2502

91) area.

The figure shows a standard normal N(0,1) distribution. Find the z value for the shaded

Version 1

A) −1.98 B) −1.87 C) −1.75 D) −1.62

92) area.

The figure shows a standard normal N(0,1) distribution. Find the z value for the shaded

A) −2.17 B) −2.09 C) −1.99 D) −1.94

Version 1

93)

The figure shows a normal N(400,23) distribution. Find the approximate shaded area.

A) .0410 B) .0501 C) .0724 D) .0838

94)

The figure shows a normal N(400,23) distribution. Find the approximate shaded area.

A) .3811 B) .3527 C) .2299 D) .1940

Version 1

95)

The figure shows a normal N(400,23) distribution. Find the x value for the shaded area.

A) 379.1 B) 362.2 C) 355.7 D) 347.6

96)

The figure shows a normal N(400,23) distribution. Find the x value for the shaded area.

Version 1

A) 412.9 B) 426.7 C) 436.2 D) 440.3

97)

The figure shows a normal N(200,50) distribution. Find the approximate shaded area.

A) .8849 B) .3527 C) .1151 D) .1444

Version 1

98)

The figure shows a normal N(200,50) distribution. Find the approximate shaded area.

A) .6915 B) .3527 C) .3085 D) .8085

99)

The figure shows a normal N(200,50) distribution. Find the approximate shaded area.

Version 1

A) .5668 B) .4332 C) .2299 D) .0668

100)

The figure shows a normal N(200,50) distribution. Find the approximate shaded area.

A) .7881 B) .7213 C) .0668 D) .5668

Version 1

101) The figure shows a normal N(200, 50) distribution. The x value for the shaded area is approximately:

A) 282 B) 227 C) 248 D) 302

102)

The figure shows a normal N(400,23) distribution. Find the x value for the shaded area.

Version 1

A) x1 = 122 andx2 = 278 B) x1 = 150 andx2 = 250 C) x1 = 102 andx2 = 298 D) x1 = 125 andx2 = 275

103) Weights of 20-foot shipping containers for residential movers are normally distributed with a mean of 27,000 pounds and a standard deviation of 3,000 pounds. What percent of the containers weigh less than 23,310 pounds?

A) .8907 B) .1093 C) .9999 D) .2216 E) .1655

104) Weights of 20-foot shipping containers have a Normal distribution with a mean of 27000 pounds and a standard deviation of 3000 pounds. What is the 97th percentile (highest 3 percent) of container weights?

A) 34,201 B) 31,806 C) 32,642 D) 21,358 E) 28,114

105) A certain type of automatic garage door will stop and reverse automatically if it encounters an object as it descends. In residential installations, the mean pressure exerted before reversal is a normally distributed random variable with a mean of 13.45 pounds and a standard deviation of 0.76 pounds. What is the probability that the pressure exerted by a randomly chosen door will exceed the mandatory safety requirement of 15 pounds before it reverses?

Version 1

A) .0207 B) .9793 C) .9501 D) .0499 E) .0998

106) The amount of sodium in a randomly chosen slice of white bread has a mean of 110 milligram with a standard deviation of 25 milligram. What is the probability that a slice contains less than 154 milligram of sodium?

A) .0392 B) .5392 C) .9608 D) .4608 E) .4419

107)

A continuous uniform distribution is always symmetric. ⊚ ⊚

108)

The height and width of a continuous uniform distribution’s PDF are the same. ⊚ ⊚

109)

true false

A continuous uniform distribution U(0,800) will have μ = 400 and σ = 230.94. ⊚ ⊚

Version 1

true false

110) A continuous uniform distribution U(100,200) will have the same standard deviation as a continuous uniform distribution U(200,300). ⊚ ⊚

111) 100.

For a continuous uniform distribution U(200,400), the parameters are μ = 300 and σ =

⊚ ⊚

112)

true false

The exponential distribution is always skewed right. ⊚ ⊚

115)

true false

The exponential distribution describes the time a salesclerk waits between two customers. ⊚ ⊚

114)

true false

The exponential distribution describes the number of arrivals per unit of time. ⊚ ⊚

113)

true false

If arrivals follow a Poisson distribution, waiting times follow the exponential distribution.

Version 1

⊚ ⊚

116)

The triangular distribution is used in "what-if" analysis for business planning. ⊚ ⊚

117)

true false

The triangular distribution T(0,10,20) is skewed left. ⊚ ⊚

119)

true false

The triangular distribution is symmetric. ⊚ ⊚

118)

true false

A triangular distribution can be skewed either left or right. ⊚ ⊚

true false

120) For a continuous random variable, the total area beneath the PDF will be greater than zero but less than one. ⊚ ⊚

Version 1

true false

121) The exponential distribution is continuous and the Poisson distribution is discrete, yet the two distributions are closely related. ⊚ ⊚

122)

The mean, median, and mode of a normal distribution will always be the same. ⊚ ⊚

123)

true false

Normal distributions differ only in their means and variances. ⊚ ⊚

125)

true false

There is a simple formula for normal areas, but we prefer a table for greater accuracy. ⊚ ⊚

124)

true false

Any normal distribution has a mean of 0 and a standard deviation of 1. ⊚ ⊚

true false

126) We would use a normal distribution to model the waiting time until the next Florida hurricane strike. ⊚ ⊚

Version 1

true false

127) In a normal distribution, the mean and standard deviation control the location and scalling of the PDF respectively. ⊚ ⊚

true false

128) Experience suggests that 4 percent of all college students have had a tonsillectomy. In a sample of 300 college students, we need to find the probability that at least 10 have had a tonsillectomy. It is acceptable to use the normal distribution to estimate this probability. ⊚ ⊚

true false

129) The normal distribution is a good approximation to the binomial when n is greater than or equal to 10. ⊚ ⊚

true false

130) The true proportion of accounts receivable with some kind of error is 4 percent for Venal Enterprises. If an auditor randomly samples 50 accounts receivable, it is acceptable to use the normal approximation to estimate the probability that fewer than two will contain errors. ⊚ ⊚

131)

true false

The normal distribution is a good approximation to the binomial if n ≥ 30. ⊚ ⊚

Version 1

true false

132)

The normal distribution is a good approximation to the binomial if n = 200 and π = .03. ⊚ ⊚

133)

The normal distribution is a good approximation to the binomial if n = 25 and π = .50. ⊚ ⊚

134)

true false

The area under a normal curve is 1 only if the distribution is standardized N(0,1). ⊚ ⊚

137)

true false

The number of lightning strikes in a day in Miami is a continuous random variable. ⊚ ⊚

136)

true false

The exponential distribution can be either right-skewed or left-skewed, depending onλ. ⊚ ⊚

135)

true false

The area under an exponential PDF can exceed 1 because the distribution is right-skewed. ⊚ ⊚

Version 1

true false

Version 1

Answer Key Test name: Chap 07_7e_Doane 1) B 2) A 3) C 4) C 5) D 6) B 7) C 8) C 9) B 10) C 11) A 12) D 13) A 14) A 15) C 16) B 17) A 18) D 19) A 20) B 21) A 22) D 23) A 24) A 25) B 26) C Version 1

27) B 28) D 29) A 30) A 31) B 32) B 33) A 34) D 35) A 36) D 37) D 38) B 39) D 40) D 41) C 42) A 43) B 44) C 45) D 46) A 47) B 48) D 49) B 50) C 51) D 52) C 53) A 54) D 55) A 56) B Version 1

57) A 58) D 59) B 60) A 61) C 62) B 63) A 64) C 65) A 66) B 67) A 68) A 69) C 70) C 71) B 72) B 73) B 74) C 75) A 76) A 77) B 78) C 79) C 80) B 81) A 82) A 83) B 84) B 85) C 86) B Version 1

87) B 88) A 89) D 90) B 91) C 92) A 93) A 94) C 95) B 96) D 97) C 98) A 99) D 100) B 101) A 102) C 103) B 104) C 105) A 106) C 107) TRUE 108) FALSE 109) TRUE 110) TRUE 111) FALSE 112) FALSE 113) TRUE 114) TRUE 115) TRUE 116) TRUE Version 1

117) FALSE 118) FALSE 119) TRUE 120) FALSE 121) TRUE 122) TRUE 123) FALSE 124) TRUE 125) FALSE 126) FALSE 127) TRUE 128) TRUE 129) FALSE 130) FALSE 131) FALSE 132) FALSE 133) TRUE 134) FALSE 135) FALSE 136) FALSE 137) FALSE

Version 1

CHAPTER 8 1)

A sampling distribution describes the distribution of

A) a parameter. B) a statistic. C) either a parameter or a statistic. D) neither a parameter nor a statistic.

As the sample size increases, the standard error of the mean

A) increases. B) decreases. C) is not affected. D) impossible to determine from this information.

Which statement is most nearly correct, other things being equal?

A) Doubling the sample size will cut the standard error of the mean in half. B) The standard error of the mean depends on the population size. C) Quadrupling the sample size roughly halves the standard error of the mean. D) The standard error of the mean depends on the confidence level.

The width of a confidence interval for μ is not affected by

A) the sample size. B) the confidence level. C) the standard deviation. D) the sample mean.

Version 1

The Central Limit Theorem implies that

A) the population will be approximately normal if n ≥ 50. B) repeated samples must be taken to obtain normality. C) the distribution of the mean is approximately normal for large n. D) the mean follows the same distribution as the population.

6) The owner of Limp Pines Resort wanted to know the average age of its clients. A random sample of 25 tourists is taken. It shows a mean age of 46 years with a standard deviation of 5 years. The width of a 98 percent confidence interval for the true mean client age is approximately

A) ±1.711 years. B) ±2.326 years. C) ±2.492 years. D) ±2.797 years.

7) In constructing a confidence interval for a mean with unknown variance with a sample of 25 items, Beth used z instead of t. "Well, at least my interval will be wider than necessary, so it was a conservative error," she said. Is Beth's statement correct?

A) Yes. B) No. C) It depends on μ. D) It depends onn.

Version 1

8) A random sample of 16 ATM transactions at the Last National Bank of Flat Rock revealed a mean transaction time of 2.8 minutes with a standard deviation of 1.2 minutes. The width (in minutes) of the 95 percent confidence interval for the true mean transaction time is

A) ±0.639. B) ±0.588. C) ±0.300. D) ±2.131.

We could narrow a 95 percent confidence interval by

A) using 99 percent confidence. B) using a larger sample. C) increasing the standard error. D) increasing the population size.

10) The owner of Torpid Oaks B&B wanted to know the average distance its guests had traveled. A random sample of 16 guests showed a mean distance of 85 miles with a standard deviation of 32 miles. The 90 percent confidence interval (in miles) for the mean is approximately

A) (71.0, 99.0). B) (71.8, 98.2). C) (74.3, 95.7). D) (68.7, 103.2).

11) A highway inspector needs an estimate of the mean weight of trucks crossing a bridge on the interstate highway system. She selects a random sample of 49 trucks and finds a mean of 15.8 tons with a sample standard deviation of 3.85 tons. The 90 percent confidence interval for the population mean is

Version 1

A) 14.72 to 16.88 tons. B) 14.90 to 16.70 tons. C) 14.69 to 16.91 tons. D) 14.88 to 16.72 tons.

12) To determine a 72 percent level of confidence for a proportion, the value of z is approximately

A) ±1.65. B) ±0.77. C) ±1.08. D) ±1.55.

13) To estimate the average annual expenses of students on books and class materials, a sample of size 36 is taken. The sample mean is $850 and the sample standard deviation is $54. A 99 percent confidence interval for the population mean is

A) $823.72 to $876.28. B) $832.36 to $867.64. C) $826.82 to $873.18. D) $825.49 to $874.51.

14) In constructing a 95 percent confidence interval, if you increase n to 4 n, the width of your confidence interval will be (assuming other things remain the same)

A) about 25 percent of its former width. B) about two times wider. C) about 50 percent of its former width. D) about four times wider.

Version 1

15)

Which of the following is not a characteristic of the t distribution?

A) It is a continuous distribution. B) It has a mean of 0. C) It is a symmetric distribution. D) It approaches z as degrees of freedom decrease.

16)

Which statement is incorrect?

A) If p = .50 and n = 100, the standard error of the sample proportion is .05. B) In a sample size calculation for estimating π, it is conservative to assume π = .50. C) If n = 250 and p = .06, we cannot assume normality in a confidence interval for π. D) Ifx = 50 andn = 100, the sample proportion is .5.

17) What is the approximate width of a 90 percent confidence interval for the true population proportion if there are 12 successes in a sample of 25?

A) ±.196 B) ±.164 C) ±.480 D) ±.206

18) A poll showed that 48 out of 120 randomly chosen graduates of California medical schools last year intended to specialize in family practice. What is the width of a 90 percent confidence interval for the proportion that plan to specialize in family practice?

Version 1

A) ±.0447 B) ±.0736 C) ±.0876 D) ±.0894

19) What is the approximate width of an 80 percent confidence interval for the true population proportion if there are 12 successes in a sample of 80?

A) ±.078 B) ±.066 C) ±.051 D) ±.094

20) A random sample of 160 commercial customers of PayMor Lumber revealed that 32 had paid their accounts within a month of billing. The 95 percent confidence interval for the true proportion of customers who pay within a month would be

A) 0.148 to 0.252. B) 0.138 to 0.262. C) 0.144 to 0.256. D) 0.153 to 0.247.

21) A random sample of 160 commercial customers of PayMor Lumber revealed that 32 had paid their accounts within a month of billing. Can normality be assumed for the sample proportion?

Version 1

A) Yes. B) No. C) need more information to say.

22) The conservative sample size required for a 95 percent confidence interval for π with an error of ±0.04 is

A) 271. B) 423. C) 385. D) 601.

23) Last week, 108 cars received parking violations in the main university parking lot. Of these, 27 had unpaid parking tickets from a previous violation. Assuming that last week was a random sample of all parking violators, find the 95 percent confidence interval for the percentage of parking violators that have prior unpaid parking tickets.

A) 18.1 to 31.9 percent B) 16.8 to 33.2 percent C) 15.3 to 34.7 percent D) 19.5 to 30.5 percent

24) In a random sample of 810 women employees, it is found that 81 would prefer working for a female boss. The width of the 95 percent confidence interval for the proportion of women who prefer a female boss is

Version 1

A) ±.0288. B) ±.0105. C) ±.0207. D) ±.0196.

25) In a random sample of 1200 college students, 387 said they prefer remote instruction. The 95 percent confidence interval for the proportion of college students who prefer remote instruction is

A) (.296, .349). B) (.288, .357). C) (.300, .345). D) (.328, .376).

26) In order to determine the true proportion of college students who prefer remote learning, what is the necessary sample size for a 90% confidence interval if the desired margin of error is ± 5%?

A) 664 B) 385 C) 271 D) 1,083

27) To estimate the average amount of time an instructor spends on a recorded lecture, a sample of 36 instructors were taken. Their reported sample mean is 94 minutes and the sample standard deviation is 18. A 95 percent confidence interval for the population mean is

Version 1

A) 86.3 to 101.7 minutes. B) 89.7 to 98.9 minutes. C) 88.9 to 99.7 minutes. D) 87.9 to 100.1 minutes.

28) A 95 percent confidence interval for the true mean time spent preparing and recording a lecture is reported to be 75 to 95 minutes. The point estimate for the true mean is

A) 80 minutes. B) 85 minutes. C) 90 minutes. D) impossible to determine.

29) A 95 percent confidence interval for the true mean time spent preparing and recording a lecture is reported to be 75 to 95 minutes. The margin of error for this estimate is

A) 10 minutes. B) 20 minutes. C) 5 minutes. D) impossible to determine.

30) Jolly Blue Giant Health Insurance (JBGHI) is concerned about rising lab test costs and would like to know what proportion of the positive lab tests for prostate cancer are actually proven correct through subsequent biopsy. JBGHI demands a sample large enough to ensure an error of ±2 percent with 90 percent confidence. What is the necessary sample size?

Version 1

A) 4,148 B) 2,401 C) 1,692 D) 1,604

31) A university wants to estimate the average distance that commuter students travel to get to class with an error of ±3 miles and 90 percent confidence. What sample size would be needed, assuming that travel distances are normally distributed with a range of X = 0 to X = 50 miles, using the Empirical Rule μ ± 3 σ to estimate σ.

A) about 28 students B) about 47 students C) about 30 students D) about 21 students

32) A financial institution wishes to estimate the mean balances owed by its credit card customers. The population standard deviation is $300. If a 99 percent confidence interval is used and an interval of ±$75 is desired, how many cardholders should be sampled?

A) 3382 B) 629 C) 87 D) 107

33) A company wants to estimate the time its trucks take to drive from city A to city B. The standard deviation is known to be 12 minutes. What sample size is required so that the error does not exceed ±2 minutes, with 95 percent confidence?

Version 1

A) 12 observations B) 139 observations C) 36 observations D) 129 observations

34) In a large lecture class, the professor announced that the scores on a recent exam were normally distributed with a range from 51 to 87. Using the Empirical Rule μ ± 3 σ to estimate σ, how many students would you need to sample to estimate the true mean score for the class with 90 percent confidence and an error of ±2?

A) about 17 students B) about 35 students C) about 188 students D) about 25 students

35) Using the conventional polling definition, find the margin of error for a customer satisfaction survey of 225 customers who have recently dined at Applebee’s.

A) ±5.0 percent B) ±4.2 percent C) ±7.1 percent D) ±6.5 percent

36) A marketing firm is asked to estimate the percentage of existing customers who would purchase a "digital upgrade" to their basic cable TV service. The firm wants 99 percent confidence and an error of ±5 percent. What is the required sample size (to the next higher integer)?

Version 1

A) 664 B) 625 C) 801 D) 957

37) An airport traffic analyst wants to estimate the proportion of daily takeoffs by small business jets (as opposed to commercial passenger jets or other aircraft) with an error of ±4 percent with 90 percent confidence. What sample size should the analyst use?

A) 385 B) 601 C) 410 D) 423

38) Ersatz Beneficial Insurance wants to estimate the cost of damage to cars due to accidents. The standard deviation of the cost is known to be $200. They want to estimate the mean cost using a 95 percent confidence interval within ±$10. What is the minimum sample size n?

A) 1083 B) 4002 C) 1537 D) 2301

39) Professor York randomly surveyed 240 students at Oxnard University and found that 150 of the students surveyed watch more than 10 hours of television weekly. Develop a 95 percent confidence interval to estimate the true proportion of students who watch more than 10 hours of television each week. The confidence interval is

Version 1

A) .533 to .717. B) .564 to .686. C) .552 to .698. D) .551 to .739.

40) Professor York randomly surveyed 240 students at Oxnard University and found that 150 of the students surveyed watch more than 10 hours of television weekly. How many additional students would Professor York have to sample to estimate the proportion of all Oxnard University students who watch more than 10 hours of television each week within ±3 percent with 99 percent confidence?

A) 761 B) 1001 C) 1489 D) 1728

41) The sample proportion is in the middle of the confidence interval for the population proportion

A) in any sample. B) only if the samples are large. C) only if π is not too far from .50. D) never.

42) For a sample of size 16, the critical values of chi-square for a 95 percent confidence interval for the population variance are

Version 1

A) 6.262, 27.49. B) 6.908, 28.85. C) 5.629, 26.12. D) 7.261, 25.00.

43) For a sample of size 11, the critical values of chi-square for a 90 percent confidence interval for the population variance are

A) 6.262, 27.49. B) 6.908, 28.85. C) 3.940, 18.31. D) 3.247, 20.48.

44) For a sample of size 18, the critical values of chi-square for a 99 percent confidence interval for the population variance are

A) 6.262, 27.49. B) 5.697, 35.72. C) 5.629, 26.12. D) 7.261, 25.00.

45)

Which of the following statements is most nearly correct, other things being equal?

A) Using Student’s t instead of z makes a confidence interval narrower. B) The table values of z and t are about the same when the mean is large. C) For a given confidence level, the z value is always smaller than the t value. D) Student’s t is rarely used because it is more conservative to use z.

Version 1

46)

The Central Limit Theorem (CLT)

A) applies only to samples from normal populations. B) applies to any population. C) applies best to populations that are skewed. D) applies only when μ and σ are known.

47) In which situation may the sample proportion safely be assumed to follow a normal distribution?

A) 12 successes in a sample of 72 items B) 8 successes in a sample of 40 items C) 6 successes in a sample of 200 items D) 4 successes in a sample of 500 items

48) In which situation may the sample proportion safely be assumed to follow a normal distribution?

A) n = 100, π = .06 B) n = 250, π = .02 C) n = 30, π = .50 D) n = 500, π = .01

49) If σ = 12, find the sample size to estimate the mean with an error of ±4 and 95 percent confidence (rounded to the next higher integer).

Version 1

A) 75 B) 35 C) 58 D) 113

50) If σ = 25, find the sample size to estimate the mean with an error of ±3 and 90 percent confidence (rounded to the next higher integer).

A) 426 B) 512 C) 267 D) 188

51)

Sampling error can be avoided

A) by using an unbiased estimator. B) by eliminating nonresponses (e.g., older people). C) by no method under the statistician’s control. D) either by using an unbiased estimator or by eliminating nonresponse.

52)

A consistent estimator for the mean

A) converges on the true parameter μ as the variance increases. B) converges on the true parameter μ as the sample size increases. C) consistently follows a normal distribution. D) is impossible to obtain using real sample data.

Version 1

53)

Concerning confidence intervals, which statement is most nearly correct?

A) We should use z instead of t when n is small. B) We use the Student’s t distribution when σ is unknown. C) We use the Student’s t distribution to narrow the confidence interval. D) Confidence intervals on proportions are rarely used in business.

54)

The standard error of the mean decreases when

A) the sample size decreases. B) the standard deviation increases. C) the standard deviation decreases or n increases. D) the population size decreases.

55)

For a given sample size, the higher the confidence level, the

A) more accurate the point estimate. B) smaller the standard error. C) smaller the interval width. D) greater the interval width.

56) A sample is taken and a confidence interval is constructed for the mean of the distribution. Which value is always found at the center of the interval?

A) the sample mean B) the population mean μ C) Neither nor μ because with a sample anything can happen D) Both and μ as long as there are not too many outliers

Version 1

57)

If a normal population has parameters μ = 40 and σ = 8, then for a sample size n = 4

A) the standard error of the sample mean is approximately 2. B) the standard error of the sample mean is approximately 4. C) the standard error of the sample mean is approximately 8. D) the standard error of the sample mean is approximately 10.

58) In a confidence interval, the finite population correction factor (FPCF) can be ignored when

A) n = 100 and N = 700. B) n = 50 and N = 200. C) n = 6 and N = 500. D) n = 8 and N = 80.

59) In a confidence interval, the finite population correction factor (FPCF) can be ignored when

A) n = 12 and N = 96. B) n = 80 and N = 400. C) n = 6 and N = 60. D) n = 8 and N = 800.

60) The expected value of an unbiased estimator is equal to the parameter whose value is being estimated. ⊚ ⊚

Version 1

true false

61)

All estimators are biased since sampling error always exists to some extent. ⊚ ⊚

62)

true false

An estimator must be unbiased if you are to use it for statistical analysis. ⊚ ⊚

true false

63) The efficiency of an estimator depends on the variance of the estimator’s sampling distribution. ⊚ ⊚

64)

true false

In comparing estimators, the more efficient estimator will have a smaller standard error. ⊚ ⊚

true false

65) A 90 percent confidence interval will be wider than a 95 percent confidence interval, ceteris paribus. ⊚ ⊚

true false

66) In constructing a confidence interval for the mean, the z distribution provides a result nearly identical to the t distribution when n is large.

Version 1

⊚ ⊚

true false

67) The Central Limit Theorem (CLT) says that, ifn exceeds 30, the population will be normal. ⊚ ⊚

true false

68) The Central Limit Theorem says that a histogram of the sample means will have a bell shape, even if the population is skewed and the sample is small. ⊚ ⊚

true false

69) A high confidence level ensures that the confidence interval will enclose the true parameter of interest. ⊚ ⊚

true false

70) The Central Limit Theorem guarantees an approximately normal sampling distribution for the mean whenn is sufficiently large. ⊚ ⊚

true false

71) A sample of size 5 shows a mean of 45.2 and a sample standard deviation of 6.4. The standard error of the sample mean is approximately 2.86. ⊚ ⊚

Version 1

true false

72)

As n increases, the width of the confidence interval will decrease, ceteris paribus. ⊚ ⊚

73)

As n increases, the standard error decreases. ⊚ ⊚

74)

true false

A higher confidence level leads to a narrower confidence interval, ceteris paribus. ⊚ ⊚

true false

75) When the sample standard deviation is used to construct a confidence interval for the mean, we would use the Student’s t distribution instead of the normal distribution. ⊚ ⊚

true false

76) When the sample size is more than one, the standard error of the sample mean will be smaller than the standard deviation of the population. ⊚ ⊚

true false

77) For a sample size of 20, a 95 percent confidence interval using the t distribution would be wider than one constructed using the z distribution.

Version 1

⊚ ⊚

true false

78) In constructing a confidence interval for a mean, the width of the interval is dependent on the sample size, the confidence level, and the population standard deviation. ⊚ ⊚

79) 30.

In constructing confidence intervals, it is conservative to use the z distribution when n ≥

⊚ ⊚

80)

true false

The distribution of the sample proportion p = x/ n is normal when n ≥ 30. ⊚ ⊚

82)

true false

The Central Limit Theorem (CLT) can be applied to the sample proportion. ⊚ ⊚

81)

true false

The standard deviation of the sample proportion p = x/ n increases as n increases. ⊚ ⊚

Version 1

true false

83) A 95 percent confidence interval constructed around p will be wider than a 90 percent confidence interval. ⊚ ⊚

true false

84) The sample proportion is always the midpoint of a confidence interval for the population proportion. ⊚ ⊚

85)

The standard error of the sample proportion is largest when π = .50. ⊚ ⊚

86)

true false

The standard error of the sample proportion does not depend on the confidence level. ⊚ ⊚

true false

87) To narrow the confidence interval for π, we can either increase n or decrease the level of confidence. ⊚ ⊚

88)

true false

Ceteris paribus, the narrowest confidence interval for π is achieved when p = .50. ⊚ ⊚

Version 1

true false

89)

Ceteris paribus, the widest confidence interval forπ is achieved whenp = .50. ⊚ ⊚

90) 10.

true false

The statistic p = x/ n may be assumed normally distributed when np ≥ 10 and n(1 − p) ≥

⊚ ⊚

true false

91) The Student’s t distribution is always symmetric and bell-shaped, but its tails lie above the normal. ⊚ ⊚

92)

true false

The confidence interval half-width when is called the margin of error. ⊚ ⊚

true false

93) Based on the Rule of Three, if no events occur in n independent trials, we can set the upper 95 percent confidence bound at 3/ n. ⊚ ⊚

Version 1

true false

94) The sample standard deviation s is halfway between the lower and upper confidence limits for the population σ (i.e., the confidence interval is symmetric around s). ⊚ ⊚

true false

95) In a sample size calculation, if the confidence level decreases, the size of the sample needed will increase. ⊚ ⊚

true false

96) To calculate the sample size needed for a survey to estimate a proportion, the population standard deviation σ must be known. ⊚ ⊚

true false

97) Assuming that π = .50 is a quick and conservative approach to use in a sample size calculation for a proportion. ⊚ ⊚

true false

98) To estimate the required sample size for a proportion, one method is to take a small pilot sample to estimate π and then apply the sample size formula. ⊚ ⊚

true false

99) The sample size needed to estimateπ is often much larger than the sample size needed to estimateµ. Version 1

⊚ ⊚

true false

100) To estimate π, you typically need a sample size equal to at least 5 percent of your population. ⊚ ⊚

true false

101) To estimate a proportion with a 4 percent margin of error and a 95 percent confidence level, the required sample size is over 800. ⊚ ⊚

true false

102) Approximately 95 percent of the population ofX values will lie within the 95 percent confidence interval for the mean. ⊚ ⊚

true false

103) A 99 percent confidence interval has higher confidence but less precision than a 95 percent confidence interval. ⊚ ⊚

104)

true false

Sampling variation is not controllable by the statistician. ⊚ ⊚

Version 1

true false

105)

The sample mean is not a random variable when the population parameters are known. ⊚ ⊚

106)

true false

The finite population correction factor (FPCF) can be ignored if n = 7 and N = 700. ⊚ ⊚

true false

107) In constructing a confidence interval, it would be important to include the finite population correction factor (FPCF) if samples of 12 items are drawn from a population of 300 items. ⊚ ⊚

true false

108) The finite population correction factor (FPCF) has an important effect when the sample size is large relative to the population size. ⊚ ⊚

true false

109) To determine the sample size to estimate a proportion or a mean, the population size is considered. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 08_7e_Doane 1) B 2) B 3) C 4) D 5) C 6) C 7) B 8) A 9) B 10) A 11) D 12) C 13) D 14) C 15) D 16) C 17) B 18) B 19) C 20) B 21) A 22) D 23) B 24) C 25) A 26) C Version 1

27) D 28) B 29) A 30) C 31) D 32) D 33) B 34) D 35) D 36) A 37) D 38) C 39) B 40) C 41) A 42) A 43) C 44) B 45) C 46) B 47) A 48) C 49) B 50) D 51) C 52) B 53) B 54) C 55) D 56) A Version 1

57) B 58) C 59) D 60) TRUE 61) FALSE 62) FALSE 63) TRUE 64) TRUE 65) FALSE 66) TRUE 67) FALSE 68) FALSE 69) FALSE 70) TRUE 71) TRUE 72) TRUE 73) TRUE 74) FALSE 75) TRUE 76) TRUE 77) TRUE 78) TRUE 79) FALSE 80) TRUE 81) FALSE 82) FALSE 83) TRUE 84) TRUE 85) TRUE 86) TRUE Version 1

87) TRUE 88) FALSE 89) TRUE 90) TRUE 91) TRUE 92) TRUE 93) TRUE 94) FALSE 95) FALSE 96) FALSE 97) TRUE 98) TRUE 99) TRUE 100) FALSE 101) FALSE 102) FALSE 103) TRUE 104) TRUE 105) FALSE 106) TRUE 107) FALSE 108) TRUE 109) FALSE

Version 1

CHAPTER 9 1) For a given sample size, when we increase the probability of a Type I error, the probability of a Type II error

A) remains unchanged. B) increases. C) decreases. D) is impossible to determine without more information.

2) to

In testing a hypothesis regarding the mean, we failed to reject H0. Thus, we are exposed

A) Type I error. B) Type II error. C) either Type I or Type II error. D) neither Type I nor Type II error.

When we reject the null hypothesis, we are exposed to

A) Type I error. B) Type II error. C) either Type I or Type II error. D) neither Type I nor Type II error.

Which statement about α is not correct?

Version 1

A) It is the probability of committing a Type I error. B) It is the test's significance level. C) It is the probability of rejecting a true H0. D) It is equal to 1 − β.

Which of the following is correct?

A) When the sample size increases, β may decrease. B) Type II error can only occur when you reject H0. C) Type I error can only occur if you fail to reject H0. D) The level of significance is the probability of Type II error.

Which of the following is incorrect?

A) The level of significance is the probability of making a Type I error. B) Lowering both α and β at once will require a larger sample size. C) The probability of failing to reject a false null hypothesis increases asn increases. D) When Type I error increases, Type II error must decrease, ceteris paribus.

7) John rejected his null hypothesis in a right-tailed test for a mean at α = .025 because his critical t value was 2.000 and his calculated t value was 2.345. We can be sure that

A) John did not commit a Type I error. B) John did not commit a Type II error. C) John committed neither a Type I nor Type II error. D) John committed both a Type I and a Type II error.

Version 1

8) "My careful physical examination shows no evidence of any serious problem," said Doctor Morpheus. "However, a very costly lab test can be performed to check for the rare condition known as estomalgia fatalis. The test is almost invariably negative for persons with your age and symptoms. My personal hypothesis is that the occasional stomach pain you reported is due to indigestion caused by eating tacos with too much hot sauce. But you must decide for yourself." Agreeing that the doctor’s hypothesis is true, you decide to forgo the expensive lab test. What would be the consequence of Type II error on your part?

A) It cannot be determined without knowing the type of test. B) Your estomalgia fatalis will go undetected. C) You will pay for a lab test that agrees with the doctor. D) Your survivors will enjoy a sizeable malpractice award.

Which of the following statements is correct?

A) Increasing α will make it more likely that we will reject H0, ceteris paribus. B) Doubling the sample size roughly doubles the test statistic, ceteris paribus. C) A higher standard deviation would increase the power of a test for a mean. D) The p-value shows the probability that the null hypothesis is false.

10) "I believe your airplane's engine is sound," states the mechanic. "I've been over it carefully, and can't see anything wrong. I'd be happy to tear the engine down completely for an internal inspection at a cost of $1,500. But I believe that roughness you heard in the engine on your last flight was probably just a bit of water in the fuel, which passed harmlessly through the engine and is now gone." If the pilot decides to have the mechanic perform the internal inspection, the cost of Type I error is

A) the pilot will experience the thrill of no-engine flight. B) the pilot will be out $1,500 unnecessarily. C) the mechanic will lose a good customer. D) impossible to determine without knowing α.

Version 1

11) A study over a 10-year period showed that 50 percent of a certain mammogram test were false positive. This indicates that

A) about half the tests indicated cancer. B) about half the tests missed a cancer that exists. C) about half the tests showed a cancer that did not exist. D) about half the women tested actually had no cancer.

12) A study over a 10-year period showed that the chance of a false positive was 50 percent. This indicates that

A) about half the women who had cancer showed no evidence of cancer. B) about half the tests missed a cancer that exists. C) about half the tests showed a cancer that did not exist. D) about half the women who were cancer-free tested positive for cancer.

13) You are driving a van packed with camping gear (total weight 3,500 pounds including yourself and family) into a northern wilderness area. You take a "short cut" that brings you to a narrow bridge above a rushing river. The bridge has a faded sign saying, "Safe Up to 2000 pounds." About a half-mile ahead, you can see that your road rejoins the main highway. If you decide to continue across the bridge rather than turning around, the cost of Type I error is

A) that you pass safely over the bridge and everyone's happy. B) that you overestimated your vehicle weight. C) that you will find out just how cold that river actually is. D) that your kids will think you are a chicken.

Version 1

14) After lowering the landing gear, the pilot notices that the "gear down and locked" light is not illuminated. "It's probably just a burned out light bulb," she says, as she proceeds on final approach for landing. Considering the pilot's decision to land without checking the landing gear, which is the result of Type I error?

A) A potentially dangerous landing, which could cause injury to passengers. B) The landing is delayed unnecessarily while the bulb is changed. C) We cannot be sure without knowing whether or not the bulb is actually faulty. D) A smooth landing, thankfully.

15) As you are crossing a field at the farm, your country cousin Jake assures you, "Don't worry about that old bull coming toward us. He's harmless." If you decide to proceed based on Jake's hypothesis, what would be Type II error on your part?

A) You will soon feel the bull's horns. B) You will run away for no good reason. C) Jake will not have any more visits from you. D) The bull will run away from you in fear.

16)

Which is not true of p-values?

A) Whenp-values are small, we tend to reject H0. B) P-values measure the probability of an incorrect decision. C) P-values allow you to make a decision without knowing if the test is one- or twotailed. D) P-values do not requireα to be specifiedapriori.

17)

For a test of a mean, which of the following is incorrect?

Version 1

A) H0 is rejected when the calculated p-value is less than the critical value of the test statistic. B) In a right-tailed test, we reject H0 when the test statistic exceeds the critical value. C) The critical value is based on the researcher's chosen level of significance. D) If H0: μ ≤ 100 and H1: μ > 100, then the test is right-tailed.

18) Guidelines for the Jolly Blue Giant Health Insurance Company say that the average hospitalization for a triple hernia operation should not exceed 30 hours. A diligent auditor studied records of 16 randomly chosen triple hernia operations at Hackmore Hospital and found a mean hospital stay of 40 hours with a standard deviation of 20 hours. "Aha!" she cried, "the average stay exceeds the guideline." At α = .025, the critical value for a right-tailed test of her hypothesis is

A) 1.753 B) 2.131 C) 1.645 D) 1.960

19) Guidelines for the Jolly Blue Giant Health Insurance Company say that the average hospitalization for a triple hernia operation should not exceed 30 hours. A diligent auditor studied records of 16 randomly chosen triple hernia operations at Hackmore Hospital and found a mean hospital stay of 40 hours with a standard deviation of 20 hours. "Aha!" she cried, "the average stay exceeds the guideline." The value of the test statistic for her hypothesis is

A) 2.080. B) 0.481. C) 1.866. D) 2.000.

Version 1

20) Guidelines for the Jolly Blue Giant Health Insurance Company say that the average hospitalization for a triple hernia operation should not exceed 30 hours. A diligent auditor studied records of 16 randomly chosen triple hernia operations at Hackmore Hospital and found a mean hospital stay of 40 hours with a standard deviation of 20 hours. "Aha!" she cried, "the average stay exceeds the guideline." The p-value for a right-tailed test of her hypothesis is

A) between .05 and .10. B) between .025 and .05. C) between .01 and .025. D) less than .01.

21) For a right-tailed test of a hypothesis for a population mean with n = 14, the value of the test statistic was t = 1.863. The p-value is

A) between .05 and .025. B) between .10 and .05. C) greater than .10. D) less than .01.

22)

Hypothesis tests for a mean using the critical value method require

A) using a two-tailed test. B) sampling a normal population. C) knowing the true population mean. D) specifying α in advance.

23)

The level of significance is not

Version 1

A) the probability of a "false rejection." B) a value between 0 and 1. C) the likelihood of rejecting the null hypothesis when it is true. D) the chance of failing to reject a true null hypothesis.

24)

The critical value in a hypothesis test

A) is calculated from the sample data. B) usually is .05 or .01 in most statistical tests. C) separates the acceptance and rejection regions. D) depends on the value of the test statistic.

25)

Which is not a likely reason to choose the z distribution for a hypothesis test of a mean?

A) The value of σ is known. B) The sample size n is very large. C) The population is normal. D) The value of σ is very large.

26) Dullco Manufacturing claims that its alkaline batteries last at least 40 hours on average in a certain type of portable CD player. But tests on a random sample of 18 batteries from a day's large production run showed a mean battery life of 37.8 hours with a standard deviation of 5.4 hours. To test DullCo's hypothesis, the test statistic is

A) −1.980 B) −1.728 C) −2.101 D) −1.960

Version 1

27) Dullco Manufacturing claims that its alkaline batteries last at least 40 hours on average in a certain type of portable CD player. But tests on a random sample of 18 batteries from a day's large production run showed a mean battery life of 37.8 hours with a standard deviation of 5.4 hours. In a left-tailed test at α = .05, which is the most accurate statement?

A) We would strongly reject the claim. B) We would clearly fail to reject the claim. C) We would face a rather close decision. D) We would switch to α = .01 for a more powerful test.

28) Dullco Manufacturing claims that its alkaline batteries last at least 40 hours on average in a certain type of portable CD player. But tests on a random sample of 18 batteries from a day's large production run showed a mean battery life of 37.8 hours with a standard deviation of 5.4 hours. To test DullCo's hypothesis, the p-value is

A) slightly less than .05. B) exactly equal to .05. C) slightly greater than .05. D) uncertain without knowing α.

29)

For tests of a mean, if other factors are held constant, which statement is correct?

A) The critical value of Student's t increases as n increases. B) A test statistic tcalc = 1.853 with n = 16 leads to rejection at α = .05 in a one-tailed test. C) It is harder to reject the null hypothesis in a two-tailed test rather than a one-tailed test. D) If we desire α = .10, then a p-value of .13 would lead us to reject the null hypothesis.

Version 1

For a sample size of n = 100, and σ = 10, we want to test the hypothesis H0: μ = 100. The 30) sample mean is 103. The test statistic is

A) 1.645. B) 1.960. C) 3.000. D) 0.300.

When testing the hypothesis H0: μ = 100 with n = 100 and σ = 100, we find that the 31) sample mean is 97. The test statistic is

A) −3.000. B) −10.00. C) −0.300. D) −0.030.

Given a normal distribution with σ = 3, we want to test the hypothesis H0: μ = 20. We 32) find that the sample mean is 21. The test statistic is

A) 1.000. B) 1.645. C) 1.960. D) impossible to find without more information.

33)

In testing a proportion, which of the following statements is incorrect?

Version 1

A) Using α = .05 rather than α = .01 would make it more likely that H0 will be rejected. B) When the sample proportion is p = .02 and n = 150, it is safe to assume normality. C) An 80 percent confidence interval is narrower than the 90 percent confidence interval, ceteris paribus. D) The sample proportion may be assumed approximately normal if the sample is large enough.

34)

Which of the following is not a characteristic of the t distribution?

A) It is a continuous distribution. B) It has a mean of zero. C) It a symmetric distribution. D) It is similar to the z distribution when n is small.

35)

Which of the following is not a valid null hypothesis?

A) H0: μ ≥ 0 B) H0: μ ≤ 0 C) H0: μ ≠ 0 D) H0: μ = 0

Given that in a one-tailed test you cannot reject H0, can you reject H0 in a two-tailed test 36) at the same α?

A) Yes. B) No. C) Only if the one-tailed test is a left-tailed test. D) Only if the one-tailed test is right-tailed test.

Version 1

37) The process that produces Sonora Bars (a type of candy) is intended to produce bars with a mean weight of 56 gram. The process standard deviation is known to be 0.77 gram. A random sample of 49 candy bars yields a mean weight of 55.82 gram. Which are the hypotheses to test whether the mean is smaller than it is supposed to be?

A) H0: μ ≤ 56, H1: μ > 56 B) H0: μ ≥ 56, H1: μ < 56 C) H0: μ = 56, H1: μ ≠ 56 D) H0: μ < 56, H1: μ ≥ 56

38) The process that produces Sonora Bars (a type of candy) is intended to produce bars with a mean weight of 56 gram. The process standard deviation is known to be 0.77 gram. A random sample of 49 candy bars yields a mean weight of 55.82 gram. Find the test statistic to see whether the candy bars are smaller than they are supposed to be.

A) −1.636 B) −1.645 C) −1.677 D) +1.636

39) The process that produces Sonora Bars (a type of candy) is intended to produce bars with a mean weight of 56 gram. The process standard deviation is known to be 0.77 gram. A random sample of 49 candy bars yields a mean weight of 55.82 gram. Find the p-value for a test to see whether the candy bars are smaller than they are supposed to be.

A) Between .05 and .10. B) Between .025 and .05. C) Between .01 and .025. D) Less than .01.

Version 1

40) A sample of 16 ATM transactions shows a mean transaction time of 67 seconds with a standard deviation of 12 seconds. Find the test statistic to decide whether the mean transaction time exceeds 60 seconds.

A) 1.457 B) 2.037 C) 2.333 D) 1.848

41) A sample of 16 ATM transactions shows a mean transaction time of 67 seconds with a standard deviation of 12 seconds. State the hypotheses to test whether the mean transaction time exceeds 60 seconds.

A) H0: μ ≤ 60, H1: μ > 60 B) H0: μ ≥ 60, H1: μ < 60 C) H0: μ = 60, H1: μ ≠ 60 D) H0: μ < 60, H1: μ ≥ 60

42) A sample of 16 ATM transactions shows a mean transaction time of 67 seconds with a standard deviation of 12 seconds. Find the critical value to test whether the mean transaction time exceeds 60 seconds at α = .01.

A) 2.947 B) 2.602 C) 2.583 D) 2.333

43)

Given H0: μ ≥ 18 and H1: μ < 18, we would commit a Type I error if we

Version 1

A) conclude that μ ≥ 18 when the truth is that μ < 18. B) conclude that μ < 18 when the truth is that μ ≥ 18. C) fail to reject μ ≥ 18 when the truth is that μ < 18. D) concludeμ ≤ 18 whenμ > 18.

44) For a right-tailed test of a hypothesis for a single population mean with n = 10, the value of the test statistic was t = 1.411. The p-value is

A) between .05 and .025. B) between .10 and .05. C) greater than .10. D) less than .001.

45) Last year, 10 percent of all teenagers purchased a new iPhone. This year, a sample of 260 randomly chosen teenagers showed that 39 had purchased a new iPhone. The test statistic to find out whether the percentage has risen would be

A) 2.687. B) 2.758. C) 0.0256. D) 2.258.

46) Last year, 10 percent of all teenagers purchased a new iPhone. This year, a sample of 260 randomly chosen teenagers showed that 39 had purchased a new iPhone. To test whether the percentage has risen, the critical value at α = .05 is

Version 1

A) 1.645. B) 1.658. C) 1.697. D) 1.960.

47) Last year, 10 percent of all teenagers purchased a new iPhone. This year, a sample of 260 randomly chosen teenagers showed that 39 had purchased a new iPhone. To test whether the percentage has risen, the p-value is approximately

A) 0.0501. B) 0.0314. C) 0.0492. D) 0.0036.

48) Ajax Peanut Butter's quality control allows 2 percent of the jars to exceed the quality standard for insect fragments. A sample of 150 jars from the current day's production reveals that 30 exceed the quality standard for insect fragments. Which is incorrect?

A) Normality of p may safely be assumed in the hypothesis test. B) A right-tailed test would be appropriate. C) We strongly suspect that quality control standards are not met. D) Type II error is more of a concern in this case than Type I error.

49) In the nation of Gondor, the EPA requires that half the new cars sold will meet a certain particulate emission standard a year later. A sample of 64 one-year-old cars revealed that only 24 met the particulate emission standard. The test statistic to see whether the proportion is below the requirement is

Version 1

A) −1.645. B) −2.066. C) −2.000. D) −1.960.

50)

The hypotheses H0: π ≥ .40, H1: π < .40 would require

A) a left-tailed test. B) a right-tailed test. C) a two-tailed test. D) either a two-tailed test or a right-tailed test work work.

51)

At α = .05, the critical value to test the hypotheses H0: π ≥ .40, H1: π < .40 would be

A) −1.645. B) −1.960. C) −2.326. D) impossible to determine without more information.

52)

In a test of a mean, the reported p-value is .025. Using α =.05 the conclusion would be to

A) accept the null hypothesis. B) reject the null hypothesis. C) fail to reject the null hypothesis. D) gather more evidence due to inconclusive results.

53)

Which of the following decisions could result in a Type II error for a test?

Version 1

A) Reject the alternative hypothesis. B) Reject the null hypothesis. C) Fail to reject the null hypothesis. D) Make no decision.

54) The Melodic Kortholt Company will change its current health plan if at least half the employees are dissatisfied with it. A trial sample of 25 employees shows that 16 are dissatisfied. In this problem

A) normality of the sample proportion should not be assumed. B) normality of the sample proportion can be assumed. C) normality of the sample proportion cannot be judged without knowing π.

55) The Melodic Kortholt Company will change its current health plan if at least half the employees are dissatisfied with it. A trial sample of 25 employees shows that 16 are dissatisfied. The p-value for a right-tailed test is

A) 0.1337. B) 0.4192. C) 0.0901. D) 0.0808.

56) The Melodic Kortholt Company will change its current health plan if at least half the employees are dissatisfied with it. A trial sample of 25 employees shows that 16 are dissatisfied. For a right-tailed test, the test statistic would be

Version 1

A) 1.227. B) 1.375. C) 1.400. D) 1.115.

57) then

If the sample size increases from 25 to 100 and the level of significance stays the same,

A) the risk of a Type II error would decrease. B) the risk of a Type I error would decrease. C) the risk of both Type I and Type II errors would decrease. D) the risk of neither Type I nor Type II error would decrease.

58) "Currently, only 20 percent of arrested drug pushers are convicted," cried candidate Courageous Calvin in a campaign speech. "Elect me and you'll see a big increase in convictions." A year after his election, a random sample of 144 case files of arrested drug pushers showed 36 convictions. For a right-tailed test, the p-value is approximately

A) 0.9332. B) 0.0668. C) 0.0435. D) 0.0250.

59)

In a right-tailed test, a statistician got a z test statistic of 1.47. What is the p-value?

A) .4292 B) .0708 C) .0874 D) .9292

Version 1

60)

In a left-tailed test, a statistician got a z test statistic of −1.720. What is the p-value?

A) .4292 B) .0709 C) .0427 D) .0301

61)

In a two-tailed test, a statistician got a z test statistic of 1.47. What is the p-value?

A) .0708 B) .1416 C) .0874 D) .0301

62)

Which of the following statements is true?

A) Decreasing α will increase the power of the test. B) Doubling the sample size will double the power of the test. C) A higher standard deviation would increase the power if we are testing a mean. D) Power of the test rises if the true mean is farther from the hypothesized mean.

63)

High power in a hypothesis test about one sample mean is likely to be associated with

A) small sample size. B) low α. C) large β. D) small σ.

Version 1

64)

The power of a test is the probability of

A) concluding H1 when H1 is true. B) concluding H1 when H0 is true. C) concluding H0 when H0 is true. D) concluding H0 when H1 is true.

65)

Which is not a step in hypothesis testing?

A) Formulate the hypotheses. B) Specify the desired Type I error. C) Find the test statistic from a table. D) Formulate a decision rule.

66)

Which is an invalid alternative hypothesis?

A) H1: μ ≠ 18 B) H1: μ = 18 C) H1: μ > 18 D) H1: μ < 18

67)

Which is a valid null hypothesis?

A) H0: μ ≠ 18 B) H0: μ = 18 C) H0: μ > 18 D) H0: μ < 18

Version 1

68)

A two-tailed hypothesis test for H0: π = .30 at α = .05 is analogous to A) asking if the 90 percent confidence interval for π contains .30. B) asking if the 95 percent confidence interval for π contains .30. C) asking if the p-value (area in both tails combined) is less than .025. D) asking if the p-value (area in both tails combined) is less than .10.

69) For a right-tailed test of hypothesis for a population mean with known σ, the test statistic was z = 1.79. The p-value is

A) 0.0367. B) 0.9633. C) 0.1186. D) 0.0179.

70)

If n = 25 and α = .05 in a right-tailed test of a mean with unknown σ, the critical value is

A) 1.960. B) 1.645. C) 1.711. D) 0.0179.

The researcher's null hypothesis is H0: σ ≤ 22. A sample of n = 25 items yields a sample 71) variance of s2 = 28.5. The critical value of chi-square for a right-tailed test at α = .05 is

Version 1

A) 1.960. B) 1.645. C) 13.85. D) 36.42.

The researcher's null hypotheses is H0: σ ≤ 22. A sample of n = 25 items yields a sample 72) variance of s2 = 28.5. The test statistic is

A) 31.09. B) 26.42. C) impossible to determine unless we know whether it is a one-tailed test. D) impossible to determine without knowingα.

The researcher's null hypothesis is H0: σ = 420. A sample of n = 18 items yields a 73) sample variance of s2 = 512. The critical values of chi-square for a two-tailed test at α = .05 are

A) 8.672 and 27.59. B) 7.564 and 30.19. C) −1.960 and +1.960. D) 9.390 and 28.87.

The researcher's null hypotheses is H0: σ = 420. A sample of n = 18 items yields a 74) sample variance of s2 = 512. The test statistic is

A) 34.09. B) 20.72. C) 14.77. D) must know α to answer.

Version 1

75)

In hypothesis testing, Type I error is

A) always set at 5 percent. B) smaller than or equal to 5 percent. C) the probability of rejecting H0 when H0 is true. D) the probability of rejecting H0 when H1 is true.

76)

In hypothesis testing, the value of β is

A) equal to 1 minus the probability of committing a Type I error. B) the probability of concluding H0 when H0 is true. C) the probability of concluding H0 when H1 is true. D) the probability concludingH1 whenH1 is true.

77) true?

Regarding the probability of Type I error ( α) and Type II error ( β), which statement is

A) β > α B) β < α C) α + β = 1 D) Power = 1 − β.

78)

In the hypothesis H0: μ = μ0, the value of μ0 is not derived from

Version 1

A) the sample. B) past experience. C) a target or benchmark . D) a scientific theory.

79)

In testing the hypotheses H0: π ≤ π0, H1: π > π0, we would use a

A) two-tailed test. B) left-tailed test. C) right-tailed test . D) breathalyzer test.

80)

We can assume that the sample proportion is normally distributed if

A) we have 10 successes in the sample. B) we have 10 failures in the sample. C) we have both 10 successes and 10 failures in the sample. D) the population is known.

81)

The critical value in a hypothesis test

A) is derived from the sample. B) is determined by α and the type of test. C) is another name for the null hypothesis . D) is a dissenting view by scientific critics.

82)

The critical value in a hypothesis test

Version 1

A) is a test statistic calculated from the sample. B) is a contradictory result from a different test. C) is a cutoff between the rejection and nonrejection regions . D) is another name for level of significance.

83)

The rejection region in a hypothesis test

A) is an area in the tail(s) of a sampling distribution. B) is a consensus formed by trained statisticians. C) is always set to correspond to α = .05 in the test. D) is always equal to the p-value in the test.

84)

A two-tailed hypothesis test

A) would not be used if the test statistic could be negative. B) will double the probability of rejecting the null hypothesis. C) is used when the direction of the test is of no research interest. D) would lead to rejection more often than a one-tailed test at the same α.

85)

Therejection region in a hypothesis test

A) is an area under the curve of a sampling distribution. B) is a consensus formed by trained statisticians. C) is always set to correspond toα = .05 in the test. D) is always equal to thep-value in the test.

86)

In a statistical test, we

Version 1

A) try to reject the null hypothesis. B) try to prove the alternative hypothesis. C) choose a null hypothesis that is easy to reject. D) choose a large level of significance if possible.

87)

The null hypothesis is

A) often from a benchmark or historical value. B) chosen after looking at the sample data. C) what the researcher is trying to prove. D) dependent on the level of significance.

88)

The decision rule is

A) based on the sampling distribution and chosen level of significance. B) specified so as to support the researcher's alternative hypothesis. C) chosen after selecting the sample and calculating the test statistic. D) specified by a panel of expert statisticians elected annually.

89)

In a left-tailed test, a statistician got a z test statistic of −1.61. What is the p-value?

A) .4292 B) .0709 C) .0537 D) .0301

90)

In a two-tailed test, a statistician got a z test statistic of 1.82. What is the p-value?

Version 1

A) .0708 B) .0688 C) .0874 D) .0301

91)

The level of significance refers to the probability of making a Type II error. ⊚ ⊚

92)

The level of significance refers to the probability of making a Type I error. ⊚ ⊚

93)

true false

A simultaneous reduction in both α and β will require a larger sample size. ⊚ ⊚

true false

94) The probability of rejecting a false null hypothesis increases as the sample size increases, other things being equal. ⊚ ⊚

true false

95) When the probability of a Type I error increases, the probability of a Type II error must decrease, ceteris paribus.

Version 1

⊚ ⊚

true false

A false positive in a drug test for steroids is a Type II error. (H0 is the hypothesis of no 96) steroid use.) ⊚ ⊚

true false

If a judge acquits every defendant, the judge will never commit a Type I error. ( H0 is the 97) hypothesis of innocence.) ⊚ ⊚

true false

98) When your sample size increases, the chance of both Type I and Type II error will increase. ⊚ ⊚

99)

A Type II error can only occur when you fail to reject H0. ⊚ ⊚

100)

true false

A Type I error can only occur if you reject H0. ⊚ ⊚

Version 1

true false

101)

John rejected H0, so we know definitely that he did not commit a Type II error. ⊚ ⊚

102)

true false

In hypothesis testing, we cannot prove a null hypothesis is true. ⊚ ⊚

true false

103) For a given level of significance ( α), increasing the sample size will increase the probability of Type II error because there are more ways to make an incorrect decision. ⊚ ⊚

true false

104) For a given sample size, reducing the level of significance will decrease the probability of making a Type II error. ⊚ ⊚

105)

The probability of a false positive is decreased if we reduce α. ⊚ ⊚

106)

true false

A hypothesis test may be statistically significant, yet have little practical importance.

Version 1

⊚ ⊚

true false

107) Compared to using α = .01, choosing α = .001 will make it less likely that a true null hypothesis will be rejected. ⊚ ⊚

true false

108) A two-tailed hypothesis test for H0: μ = 15 at α = .10 is analogous to asking if a 90 percent confidence interval for μ contains 15. ⊚ ⊚

109)

For a given sample size and α level, the Student's t value always exceeds the z value. ⊚ ⊚

110)

true false

For a given level of significance, the critical value of Student's t increases as n increases. ⊚ ⊚

true false

111) For a sample of nine items, the critical value of Student's t for a left-tailed test of a mean at α = .05 is −1.860. ⊚ ⊚

Version 1

true false

112) Holding other factors constant, it is harder to reject the null hypothesis for a mean when conducting a two-tailed test rather than a one-tailed test. ⊚ ⊚

113)

If we choose α = .10, then a p-value of .13 would lead us to reject the null hypothesis. ⊚ ⊚

114) true.

true false

The p-value is the probability of the sample result (or one more extreme), assuming H0 is ⊚ ⊚

115)

true false

The probability of rejecting a true null hypothesis is the significance level of the test. ⊚ ⊚

true false

116) A null hypothesis is rejected when the calculated p-value is less than the critical value of the test statistic. ⊚ ⊚

Version 1

true false

117) In a right-tailed test, the null hypothesis is rejected when the value of the test statistic exceeds the critical value. ⊚ ⊚

true false

118) The critical value of a hypothesis test is based on the researcher's selected level of significance. ⊚ ⊚

true false

119) If the null and alternative hypotheses are H0: μ ≤ 100 and H1: μ > 100, the test is righttailed. ⊚ ⊚

120)

true false

The null hypothesis is rejected when the p-value exceeds the level of significance. ⊚ ⊚

true false

121) For a given null hypothesis and level of significance, the critical value for a two-tailed test is greater than the critical value for a one-tailed test. ⊚ ⊚

true false

122) For a given H0 and level of significance, if you reject the H0 for a one-tailed test, you would also reject H0 for a two-tailed test.

Version 1

⊚ ⊚

true false

123) If the hypothesized proportion is π0 = .025 in a sample of size 120, it is safe to assume normality of the sample proportion p. ⊚ ⊚

124)

For a mean, we would expect the test statistic to be near zero if the null hypothesis is true. ⊚ ⊚

125)

true false

To test the hypothesis H0: π = .0125 using n = 160, it is safe to assume normality of p. ⊚ ⊚

128)

true false

In testing the hypotheses H0: π ≤ π0, H1: π > π0, we would use a right-tailed test. ⊚ ⊚

127)

true false

In the hypothesis H0: π = π0, the value of π0 is derived from the sample. ⊚ ⊚

126)

true false

In testing a proportion, normality of p can be assumed if nπ0 ≥ 10 and n(1 − π0) ≥ 10.

Version 1

⊚ ⊚

129) − β.

Power is the probability of rejecting the null hypothesis when it is false and is equal to 1

⊚ ⊚

130)

true false

The power curve plots β on the y-axis and the test statistic on the x-axis. ⊚ ⊚

134)

true false

The height of the power curve shows the probability of accepting a true null hypothesis. ⊚ ⊚

133)

true false

The power of a test is the probability that the test will reject a false null hypothesis. ⊚ ⊚

132)

true false

Other things being equal, a smaller standard deviation implies higher power. ⊚ ⊚

131)

true false

A smaller probability of Type II error implies higher power of the test.

Version 1

⊚ ⊚

135)

Varying the true mean is a movement along the power curve, not a shift in the curve. ⊚ ⊚

136)

true false

Larger samples lead to increased power, ceteris paribus. ⊚ ⊚

140)

true false

A power curve for a mean is at its lowest point when the true μ is very near μ0. ⊚ ⊚

139)

true false

Increasing the level of significance shifts the power curve upward, ceteris paribus. ⊚ ⊚

138)

true false

Increasing the sample size shifts the power curve upward, ceteris paribus. ⊚ ⊚

137)

true false

In graphing power curves, there is a different power curve for each sample size n.

Version 1

⊚ ⊚

141)

In hypothesis testing, we are trying to reject the alternative hypothesis. ⊚ ⊚

142)

true false

When σ is unknown, it is more conservative to use z instead of t for the critical value. ⊚ ⊚

144)

true false

In hypothesis testing, we are trying to prove the null hypothesis. ⊚ ⊚

143)

true false

If we chooseα = .10, then ap-value = .078 would lead us to reject the null hypothesis. ⊚ ⊚

true false

145) If we chooseα = .10 in a two-tailed test, then ap-value = .078 would lead us to fail to reject the null hypothesis. ⊚ ⊚

146)

true false

If the lower tail area for a left-tailed test is .023, then thep-value = .023.

Version 1

⊚ ⊚

147)

If the lower tail area for a right-tailed test is .023, then thep-value = .023. ⊚ ⊚

148)

true false

If the lower tail area for a two-tailed test is .023, then thep-value = .023. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 09_7e_Doane 1) C 2) B 3) A 4) D 5) A 6) C 7) B 8) B 9) A 10) B 11) C 12) D 13) C 14) A 15) A 16) B 17) A 18) B 19) D 20) B 21) A 22) D 23) D 24) C 25) D 26) B Version 1

27) C 28) C 29) C 30) C 31) A 32) D 33) B 34) D 35) C 36) B 37) B 38) A 39) A 40) C 41) A 42) B 43) B 44) B 45) A 46) A 47) D 48) A 49) C 50) A 51) A 52) B 53) C 54) B 55) D 56) C Version 1

57) A 58) B 59) B 60) C 61) B 62) D 63) D 64) A 65) C 66) B 67) B 68) B 69) A 70) C 71) D 72) A 73) B 74) B 75) C 76) C 77) D 78) A 79) C 80) C 81) B 82) C 83) A 84) C 85) A 86) A Version 1

87) A 88) A 89) C 90) B 91) FALSE 92) TRUE 93) TRUE 94) TRUE 95) TRUE 96) FALSE 97) TRUE 98) FALSE 99) TRUE 100) TRUE 101) TRUE 102) TRUE 103) FALSE 104) FALSE 105) TRUE 106) TRUE 107) TRUE 108) TRUE 109) TRUE 110) FALSE 111) TRUE 112) TRUE 113) FALSE 114) TRUE 115) TRUE 116) FALSE Version 1

117) TRUE 118) TRUE 119) TRUE 120) FALSE 121) TRUE 122) FALSE 123) FALSE 124) TRUE 125) FALSE 126) TRUE 127) FALSE 128) TRUE 129) TRUE 130) TRUE 131) TRUE 132) FALSE 133) FALSE 134) TRUE 135) TRUE 136) TRUE 137) TRUE 138) TRUE 139) TRUE 140) TRUE 141) FALSE 142) FALSE 143) FALSE 144) TRUE 145) FALSE 146) TRUE Version 1

147) FALSE 148) FALSE

Version 1

CHAPTER 10 1) In a right-tailed test comparing two proportions, the test statistic was zcalc = +1.81. The pvalue is

A) 0.9649. B) 0.0351. C) 0.4649. D) Must know n to answer.

2) In a left-tailed test comparing two means with unknown variances assumed to be equal, the test statistic was t = −1.81 with sample sizes of n1 = 8 and n2 = 12. The p-value would be

A) between .025 and .05. B) between .01 and .025. C) between .05 and .10. D) Must know α to answer.

3) In a left-tailed test comparing two means with variances unknown but assumed to be equal, the sample sizes weren1 = 8 andn2 = 12. Atα = .05, the critical value would be

A) −1.960. B) −2.101. C) −1.734. D) −1.645.

4) In a right-tailed test comparing two means with known variances, the sample sizes were n1 = 8 and n2 = 12. At α = .05, the critical value would be

Version 1

A) 1.960. B) 1.645. C) 1.734. D) 1.282.

5) In a test for equality of two proportions, the sample proportions were p1 = 12/50 and p2 = 18/50. The test statistic is

A) −1.44. B) −1.31. C) −1.67. D) Impossible to determine without knowingα.

6) In a test for equality of two proportions, the sample proportions were p1 = 12/50 and p2 = 18/50. The pooled proportion is

A) 0.20. B) 0.24. C) 0.36. D) 0.30.

7) If the sample proportions were p1 = 12/50 and p2 = 18/50, what is the approximate 95 percent confidence interval for the difference of the population proportions?

A) [−.144, +.244] B) [−.120, +.120] C) [−.298, +.058] D) [−.011, .214]

Version 1

8) John wants to compare two means. His sample statistics were 1 = 22.7,s12 = 5.4n1 = 9 and 2 = 20.5, s22 = 3.6, n2 = 9. Assuming equal variances, which is the approximate 95 percent confidence interval for the difference of the population means?

A) [2.44, 6.19] B) [1.17, 5.08] C) [0.08, 4.32] D) [−0.09, 3.19]

9) Kate wants to compare two means. Her sample statistics were 1 = 22.7,s12 = 5.4,n1 = 9 and 2 = 20.5,s22 = 3.6,n2 = 9. Assuming equal variances, the pooled variance is

A) 4.5. B) 4.9. C) 5.1. D) 3.8.

10) John wants to compare two means. His sample statistics were 1 = 22.7,s12 = 5.4,n1 = 9 and 2 = 20.5,s22 = 3.6,n2 = 9. Assuming equal variances, the test statistic is

A) 2.37. B) 2.20. C) 1.96. D) Must know α to answer.

11) Kate wants to compare two means. Her sample statistics were 1 = 22.7,s12 = 5.4,n1 = 9 and 2 = 20.5,s22 = 3.6,n2 = 9. Assuming equal variances, the degrees of freedom for his test will be

Version 1

A) 16. B) 18. C) 9. D) 8.

12) In a random sample of patient records in Cutter Memorial Hospital, six-month postoperative exams were given in 90 out of 200 prostatectomy patients, while in Paymor Hospital such exams were given in 110 out of 200 cases. In comparing these two proportions, normality of the difference may be assumed because

A) the populations are large enough to be assumed normal. B) the probability of success can reasonably be assumed constant. C) the samples are random, so the proportions are unbiased estimates. D) nπ ≥ 10 and n(1 − π) ≥ 10 for each sample taken separately.

13) In a random sample of patient records in Cutter Memorial Hospital, six-month postoperative exams were given in 90 out of 200 prostatectomy patients, while in Paymor Hospital such exams were given in 110 out of 200 cases. In a left-tailed test for equality of proportions, the test statistic is

A) −1.96. B) −2.00. C) −4.00. D) −3.48.

14) In a random sample of patient records in Cutter Memorial Hospital, six-month postoperative exams were given in 90 out of 200 prostatectomy patients, while in Paymor Hospital such exams were given in 110 out of 200 cases. In a left-tailed test for equality of proportions, the p-value is

Version 1

A) 0.9772. B) 0.0228. C) 0.4772. D) 0.0517.

15) In a random sample of patient records in Cutter Memorial Hospital, six-month postoperative exams were given in 90 out of 200 cases, while in Paymor Hospital such exams were given in 110 out of 200 cases. The pooled proportion is

A) 0.50. B) 0.40. C) 0.30. D) 0.20.

16) Management of Melodic Kortholt Company compared absenteeism rates in two plants on the third Monday in November. Of Plant A’s 800 employees, 120 were absent. Of Plant B’s 1200 employees, 144 were absent. To compare the two proportions, the pooled proportion is

A) 0.130. B) 0.140. C) 0.132. D) 0.135.

17) Management of Melodic Kortholt Company compared absenteeism rates in two plants on the third Monday in November. Of Plant A’s 800 employees, 120 were absent. Of Plant B’s 1200 employees, 144 were absent. MegaStat’s results for a two-tailed test are shown below.

Version 1

0.15

0.12

p (as decimal)

120/800

144/1200

p (as fraction)

120

144

800

1200

0.03 sample difference 0.00 hypothesized difference 0.01545 standard error x.xx z .0522 p-value (two-tailed)

The test statistic (shown as z = x.xx) is approximately A) 2.022. B) 1.960. C) 1.942. D) 1.645.

18) Management of Melodic Kortholt Company compared absenteeism rates in two plants on the third Monday in November. Of Plant A’s 800 employees, 120 were absent. Of Plant B’s 1200 employees, 144 were absent. MegaStat’s results for a two-tailed test are shown below. p1

0.15

0.12

p (as decimal)

120/800

144/1200

p (as fraction)

120

144

800

1200

Version 1

0.03 sample difference 0.00 hypothesized difference 0.01545 standard error x.xx z .0522 p-value (two-tailed)

At α = .05, the two-tailed test for a difference in proportions is A) just barely significant. B) not quite significant. C) not feasible due to nonnormality. D) not appropriate becausep1 >p2.

19) A new policy of "flex hours" is proposed. Random sampling showed that 28 of 50 female workers favored the change, while 22 of 50 male workers favored the change. Management wonders if there is a difference between the two groups. For a test comparing the two proportions, the assumption of normality for the difference of proportions is

A) clearly justified. B) clearly unjustified. C) a borderline call. D) Normality is always assumed if sample sizes are equal.

20) A new policy of "flex hours" is proposed. Random sampling showed that 28 of 50 female workers favored the change, while 22 of 50 male workers favored the change. Management wonders if there is a difference between the two groups. What is the test statistic to test for a zero difference in the population proportions?

Version 1

A) 1.321 B) 1.287 C) 1.200 D) −1.255

21) A new policy of "flex hours" is proposed. Random sampling showed that 28 of 50 female workers favored the change, while 22 of 50 male workers favored the change. Management wonders if there is a difference between the two groups. What is the p-value for a two-tailed test?

A) .3849 B) .1151 C) .2301 D) .3453

22) At Huge University, a sample of 200 business school seniors showed that 26 planned to pursue an MBA degree, compared with 120 of 800 arts and sciences seniors. We want to know if the proportion is higher in the arts and sciences group. The pooled proportion for this test is

A) 0.130. B) 0.140. C) 0.145. D) 0.146.

23) At Huge University, a sample of 200 business school seniors showed that 26 planned to pursue an MBA degree, compared with 120 of 800 arts and sciences seniors. We want to know if the proportion is higher in the arts and sciences group. For this test, the assumption of normality for the difference of proportions is

Version 1

A) clearly unjustified. B) clearly justified. C) a borderline call. D) normality is never justified when sample sizes are not equal.

24) At Huge University, a sample of 200 business school seniors showed that 26 planned to pursue an MBA degree, compared with 120 of 800 arts and sciences seniors. We want to know if the proportion is higher in the arts and sciences group. What is the z test statistic?

A) −1.322. B) −1.122. C) −0.716. D) We must first knowα.

25) At Huge University, a sample of 200 business school seniors showed that 26 planned to pursue an MBA degree, compared with 120 of 800 arts and sciences seniors. We want to know if the proportion is higher in the arts and sciences group. The p-value for a left-tailed test is approximately

A) 0.38. B) 0.48. C) 0.24. D) 0.51.

26) Two well-known aviation training schools are being compared using random samples of their graduates. It is found that 70 of 140 graduates of Fly-More Academy passed their FAA exams on the first try, compared with 104 of 260 graduates of Blue Yonder Institute. To compare the pass rates, the pooled proportion would be

Version 1

A) 0.500. B) 0.435. C) 0.400. D) 0.345.

27) Two well-known aviation training schools are being compared using random samples of their graduates. It is found that 70 of 140 graduates of Fly-More Academy passed their FAA exams on the first try, compared with 104 of 260 graduates of Blue Yonder Institute. To compare the two proportions, the assumption of normality of the test statistic is

A) justified, but it is a borderline case. B) clearly justified. C) clearly not justified. D) normality is never justified if sample sizes are unequal.

28) Two well-known aviation training schools are being compared using random samples of their graduates. It is found that 70 of 140 graduates of Fly-More Academy passed their FAA exams on the first try, compared with 104 of 260 graduates of Blue Yonder Institute. The test statistic to test the pass rates for equality is

A) 2.141. B) 1.298. C) 1.227. D) 1.924.

29) Two well-known aviation training schools are being compared using random samples of their graduates. It is found that 70 of 140 graduates of Fly-More Academy passed their FAA exams on the first try, compared with 104 of 260 graduates of Blue Yonder Institute. To compare the pass rates, find the critical value for a right-tailed test at α = .05.

Version 1

A) 1.960 B) 1.645 C) 2.326 D) 1.28

30) Two well-known aviation training schools are being compared using random samples of their graduates. It is found that 70 of 140 graduates of Fly-More Academy passed their FAA exams on the first try, compared with 104 of 260 graduates of Blue Yonder Institute. To compare the pass rates, the p-value for a right-tailed test is approximately

A) 0.054. B) 0.027. C) 0.155. D) 0.013.

31) Two well-known aviation training schools are being compared using random samples of their graduates. It is found that 70 of 140 graduates of Fly-More Academy passed their FAA exams on the first try, compared with 104 of 260 graduates of Blue Yonder Institute. In a righttailed test, the p-value is .0275, so at α = .025 we should

A) reject the hypothesis of equal proportions. B) not reject the hypothesis of equal proportions. C) change the α to .05 to get a rejection. D) accept our sample as proof that the proportions are equal.

32) Of 200 youthful gamers (under 18) who tried the new Z-Box-Plus game, 160 rated it "excellent," compared with only 144 of 200 adult gamers (18 or over). The pooled proportion for a test to compare the two proportions would be

Version 1

A) 0.76. B) 0.72. C) 0.77. D) Must know α to answer.

33) Of 200 youthful gamers (under 18) who tried the new Z-Box-Plus game, 160 rated it "excellent," compared with only 144 of 200 adult gamers (18 or over). The test statistic to test the two proportions for equality would be

A) 1.645. B) 1.960. C) 1.873. D) 1.448.

34) Of 200 youthful gamers (under 18) who tried the new Z-Box-Plus game, 160 rated it "excellent," compared with only 144 of 200 adult gamers (18 or over). The p-value for a righttailed test to compare the two proportions would be approximately

A) 0.042. B) 0.031. C) 0.054. D) 0.095.

35) Of 200 youthful gamers (under 18) who tried the new Z-Box-Plus game, 160 rated it "excellent," compared with only 144 of 200 adult gamers (18 or over). Calculate the 95 percent confidence interval for the difference of proportions.

Version 1

A) [+.013, +.263] B) [−.014, +.188] C) [−.003, +.163] D) [+.057, +.261]

36) Carver Memorial Hospital’s surgeons have a new procedure that they think will decrease the time to perform an appendectomy. A sample of 8 appendectomies using the old method had a mean of 38 minutes with a variance of 36 minutes, while a sample of 10 appendectomies using the experimental method had a mean of 29 minutes with a variance of 16 minutes. For a righttailed test for equal means (assume equal variances), the critical value at α = .10 is

A) 1.746. B) 1.337. C) 2.120. D) 2.754.

37) Carver Memorial Hospital’s surgeons have a new procedure that they think will decrease the time to perform an appendectomy. A sample of 8 appendectomies using the old method had a mean of 38 minutes with a variance of 36 minutes, while a sample of 10 appendectomies using the experimental method had a mean of 29 minutes with a variance of 16 minutes. For a righttailed test of equal means (assume equal variances), the pooled variance is

A) 14.76. B) 26.00. C) 24.75. D) 27.54.

Version 1

38) Carver Memorial Hospital’s surgeons have a new procedure that they think will decrease the time to perform an appendectomy. A sample of 8 appendectomies using the old method had a mean of 38 minutes with a variance of 36 minutes, while a sample of 10 appendectomies using the experimental method had a mean of 29 minutes with a variance of 16 minutes. For a righttailed test of means (assume equal variances), the test statistic is

A) 3.814. B) 2.365. C) 3.000. D) 1.895.

39) Based on a random sample of 13 tire changes, the mean time to change a tire on a Boeing 777 has a mean of 59.5 minutes with a standard deviation of 8.4 minutes. For 10 tire changes on a Boeing 787, the mean time was 64.3 minutes with a standard deviation of 12.4 minutes. To test for equal variances in a two-tailed test at α = .10, the critical values are

A) 3.73 and 0.228. B) 2.51 and 3.67. C) 3.07 and 0.398. D) 3.07 and 0.357.

40) A certain psychological theory predicts that men want bigger families than women. Kate asked each student in her psychology class how many children he or she considered ideal for a married couple and obtained the Excel results shown below at α = .05. Desired Number of Children t-Test: Two-sample Assuming Equal Variances Men Mean Variance Observations Pooled Variance

Version 1

2.4571 0.7261 35 0.59206

Women 2.1333 0.2667 15

Hypothesized Diff

t Stat

1.364

P(T <= t) one-tail

0.090

t Critical one-tail

1.677

P(T <= t) two-tail

0.179

t Critical two-tail

2.011

t-Test: Two-sample Assuming Unequal Variances Men Mean Variance Observations Hypothesized Diff df

Women

2.4571 0.7261 35 0

2.1333 0.2667 15

t Stat

1.650

P(T <= t) one-tail

0.053

t Critical one-tail

1.682

P(T <= t) two-tail

0.106

t Critical two-tail

2.018

What conclusion can you draw in a two-tailed test at α = .05? A) Men want larger families on average than women. B) Women want larger families on average than men. C) We cannot reject the hypothesis of equal population means. D) The decision depends on whether or not the variances are equal.

Version 1

41) Nacirema Airlines is buying a fleet of new fuel-efficient planes. The HogJet and the LitheJet both meet their price and performance needs, and both planes meet EPA noise guidelines. However, the quieter plane is preferred. Each plane is flown through a typical takeoff and landing sequence 10 times, while remote sensors at ground level record the noise levels (in decibels). The table below summarizes the sound level tests using Excel’s default level of significance ( α = .05). t-Test Assuming Equal Variances LitheJet

HogJet

Mean Variance Observations Pooled Variance

80.3368 0.7178 10 2.7282

Hypothesized Diff

0.0000

82.4669 4.7385 10

t Stat

−2.8837

P(T <= t) one-tail

0.0049

t Critical one-tail

1.7341

P(T <= t) two-tail

0.0099

t Critical two-tail

2.1009

t-Test Assuming Unequal Variances LitheJet Mean Variance Observations Hypothesized Diff df

HogJet

80.3368 0.7178 10 12 0

t Stat

−2.8837

P(T <= t) one-tail

0.0069

t Critical one-tail

1.7823

Version 1

82.4669 4.7385 10

P(T <= t) two-tail

0.0137

t Critical two-tail

2.1778

In a left-tailed test comparing the means at α = .05, we would A) not reject H0. B) reject H0. C) have insufficient information to make a decision. D) rejectH1.

42) Nacirema Airlines is buying a fleet of new fuel-efficient planes. The HogJet and the LitheJet both meet their price and performance needs, and both planes meet EPA noise guidelines. However, the quieter plane is preferred. Each plane is flown through a typical takeoff and landing sequence 10 times, while remote sensors at ground level record the noise levels (in decibels). The table below summarizes the sound level tests using Excel’s default level of significance ( α = .05). t-Test Assuming Equal Variances LitheJet

HogJet

Mean Variance Observations Pooled Variance

80.3368 0.7178 10 2.7282

Hypothesized Diff

0.0000

82.4669 4.7385 10

t Stat

−2.8837

P(T <= t) one-tail

0.0049

t Critical one-tail

1.7341

P(T <= t) two-tail

0.0099

t Critical two-tail

2.1009

t-Test Assuming Unequal Variances

Version 1

LitheJet Mean Variance Observations Hypothesized Diff

HogJet

80.3368 0.7178 10 12

82.4669 4.7385 10

t Stat

−2.8837

P(T <= t) one-tail

0.0069

t Critical one-tail

1.7823

P(T <= t) two-tail

0.0137

t Critical two-tail

2.1778

After inspecting this table, we would most likely

A) use the test assuming unequal variances. B) use the test for equal variances. C) perform another test to determine if the variances are equal before proceeding. D) realize that the decision is not affected by our assumptions concerning the variance.

43) Nacirema Airlines is buying a fleet of new fuel-efficient planes. The HogJet and the LitheJet both meet their price and performance needs, and both planes meet EPA noise guidelines. However, the quieter plane is preferred. Each plane is flown through a typical takeoff and landing sequence 10 times, while remote sensors at ground level record the noise levels (in decibels). The table below summarizes the sound level tests using Excel’s default level of significance ( α = .05). t-Test Assuming Equal Variances LitheJet Mean Variance

Version 1

80.3368 0.7178

HogJet 82.4669 4.7385

Observations Pooled Variance

10 2.7282

Hypothesized Diff

0.0000

t Stat

−2.8837

P(T <= t) one-tail

0.0049

t Critical one-tail

1.7341

P(T <= t) two-tail

0.0099

t Critical two-tail

2.1009

t-Test Assuming Unequal Variances LitheJet Mean Variance Observations Hypothesized Diff df

HogJet

80.3368 0.7178 10 12

82.4669 4.7385 10

t Stat

−2.8837

P(T <= t) one-tail

0.0069

t Critical one-tail

1.7823

P(T <= t) two-tail

0.0137

t Critical two-tail

2.1778

If we switched from α = .05 to α = .005 in a two-tailed test of means, our assumption about variances (assumed equal or assumed unequal) would

Version 1

A) affect the decision. B) not affect the decision. C) require a new analysis. D) increase the power of the test.

44)

A psychology researcher has a theory that predicts women will tend to carry more cash

than men. If we define the sample statistic as lead us to perform

theresearcher's hypothesis would

A) a right-tailed test. B) a left-tailed test. C) a two-tailed test. D) either a right- or left-tailed test.

45) A psychology researcher has a theory that predicts women will tend to carry more cash than men. A random sample of Ersatz University students revealed that 16 females had a mean of $22.30 in their wallets with a standard deviation of $3.20, while 16 males had a mean of $17.30 with a standard deviation of $9.60. If we define the sample statistic as correct set of hypotheses would be

, the

A) H0:μwomen −μmen > 0 vsH1:μwomen −μmen ≤ 0. B) H0:μwomen −μmen ≤ 0 vsH1:μwomen −μmen > 0. C) H0:μwomen −μmen < 0 vsH1:μwomen −μmen ≥ 0. D) H0:μwomen −μmen = 0 vsH1:μwomen −μmen ≠ 0.

46) A psychology researcher has a theory that predicts women will tend to carry more cash than men. A random sample of Ersatz University students revealed that 16 females had a mean of $22.30 in their wallets with a standard deviation of $3.20, while 16 males had a mean of $17.30 with a standard deviation of $9.60. The test statistic for the researcher’s hypothesis is

Version 1

A) impossible to determine without knowing α. B) 1.250. C) 1.504. D) 1.976.

47) A random sample of Ersatz University students revealed that 16 females had a mean of $22.30 in their wallets with a standard deviation of $3.20, while 16 males had a mean of $17.30 with a standard deviation of $9.60. In comparing the population variances at α = .10 in a twotailed test, we conclude that

A) the variances are equal. B) the variances are unequal. C) the variances are incomparable (different sample sizes).

48) Randomly chosen MBA students were asked their opinions about the ideal number of children for a married couple. The sample data were entered into MegaStat, and the following results were produced.

Men

Hypothesis Test: independent Groups (t-test, unequal variance) Women

2.812 1.2505 11

2.1538 mean 0.5547 standard deviation 13 sample size 13 pooled df

difference (Men − Women) standard error of difference hypothesized difference t p- value (one-tailed, upper)

Version 1

0.6582 0.40722 0 1.62 0.065

F-test for equality of variance variance: Men variance: Women F p- value

1.56375 0.307692 5.08 0.01

To compare the means, would it be appropriate to use a test that assumes equal variances? A) Yes, because by pooling our variances, we can simplify our calculations. B) Yes, we should assume equal variances when comparing independent samples. C) No, because the sample statistics show that the variances are unequal atα = .05. D) No, because the variances will differ because the means differ significantly.

49) Litter sizes (number of pups) for randomly chosen dogs from two breeds were compared. The sample data were entered into Excel, and the following results were produced. t-Test: Two-Sample Assuming Unequal Variances Dalmatian Labrador Mean Variance Observations Hypothesized Mean Difference df

4.8125 3.4958333 16 0

5.461538 0.602564 13

t Stat

−1.261183

What is the critical value for a left-tailed test comparing the means at α = .05? A) −1.645 B) −1.721 C) −1.803 D) −1.699

Version 1

50) Randomly chosen MBA students were asked their opinions about the ideal number of children for a married couple. The sample data were entered into MegaStat, and the following results were produced.

Men

Hypothesis Test: independent Groups (t-test, unequal variance) Women

2.812 1.2505 11

2.1538 mean 0.5547 standard deviation 13 sample size 13 pooled df

difference (Men − Women) standard error of difference hypothesized difference t p- value (one-tailed, upper)

F-test for equality of variance variance: Men variance: Women F p- value

0.6582 0.40722 0 1.62 0.065

1.56375 0.307692 5.08 0.01

What conclusion can you draw from this analysis at α = .05? A) Men want larger families on average than women. B) Women want larger families on average than men. C) This is insufficient evidence to suggest a difference in means. D) We could conclude that men want larger families if we used a two-tailed test.

51) Litter sizes (number of pups) for randomly chosen dogs from two breeds were compared. The sample data were entered into Excel, and the following results were produced. t-Test: Two-Sample Assuming Unequal Variances Dalmatian Labrador

Version 1

Mean Variance Observations Hypothesized Mean Diff df

4.8125 3.4958333 16 0

5.461538 0.602564 13

t Stat

−1.261183

What is the p-value for a left-tailed test comparing the means at α = .05? A) less than .10. B) more than .10. C) between .10 and .05. D) between .05 and .01.

52) During a test period, an experimental group of 10 vehicles using an 85 percent ethanolgasoline mixture showed mean CO2 emissions of 667 pounds per 1000 miles, with a standard deviation of 20 pounds. A control group of 14 vehicles using regular gasoline showed mean CO2 emissions of 679 pounds per 1000 miles with a standard deviation of 15 pounds. At α = .05, in a left-tailed test, the critical value to compare the means (assuming equal variances) is

A) −2.508. B) −2.074. C) −1.321. D) −1.717.

53) During a test period, an experimental group of 10 vehicles using an 85 percent ethanolgasoline mixture showed mean CO2 emissions of 667 pounds per 1000 miles, with a standard deviation of 20 pounds. A control group of 14 vehicles using regular gasoline showed mean CO2 emissions of 679 pounds per 1000 miles with a standard deviation of 15 pounds. Assuming equal variances, the pooled variance is

Version 1

A) 296.59. B) 225.00. C) 400.00. D) 522.16.

54) During a test period, an experimental group of 10 vehicles using an 85 percent ethanolgasoline mixture showed mean CO2 emissions of 667 pounds per 1000 miles, with a standard deviation of 20 pounds. A control group of 14 vehicles using regular gasoline showed mean CO2 emissions of 679 pounds per 1000 miles with a standard deviation of 15 pounds. At α = .05, in a left-tailed test (assuming equal variances) the test statistic is

A) −1.310. B) −2.042. C) −1.645. D) −1.683.

55) During a test period, an experimental group of 10 vehicles using an 85 percent ethanolgasoline mixture showed mean CO2 emissions of 240 pounds per 100 miles, with a standard deviation of 17 pounds. A control group of 14 vehicles using regular gasoline showed mean CO2 emissions of 252 pounds per 100 miles with a standard deviation of 15 pounds. A quick comparison of the sample variances suggests that

A) the population variances are probably equal. B) the population variance for the 85 percent mixture is probably greater. C) incomparable. D) the population variance for the regular gasoline is greater.

56) Mary did an analysis of variances in samples of acute care occupancy rates at two community hospitals and obtained the following results:

Version 1

F-test for equality of variance variance: group 1 variance: group 1 F p- value

108.243 98.371 1.100 0.905

Can Mary conclude that the variances are unequal at α = .05? A) No, there is not enough evidence to believe the variances are unequal. B) Yes, the analysis shows that the variances are unequal. C) You cannot tell without knowing the sample sizes. D) Mary should have conducted a left tailed test to conclude they were unequal.

57) Mary analyzed occupancy rates at two community hospitals and obtained the following Excel results. t-Test for Acue Care Occupancy Rates MaxHealth Mean Variance Observations Hypothesized Diff

62.5462 108.2377 13 0

HealthPro 68.4800 98.3707 10

t Stat

−1.3923

P(T<=t) one-tail

0.0896

t Critical one-tail

1.7247

P(T<=t) two-tail

0.1791

t Critical two-tail

2.0860

Which conclusion is correct in a two-tailed test at α = .05?

Version 1

A) There appears to be no difference in the mean occupancy rates. B) HealthPro has a significantly higher mean occupancy rate. C) There is a significant difference in the mean occupancy rates. D) MaxHealth has a significantly lower mean occupancy rate.

58) A medical researcher wondered if there is a significant difference between the mean birth weight of boy and girl babies. Random samples of 5 babies’ weights (pounds) for each gender showed the following: Boys Girls

8.0 5.3

4.7 2.8

7.3 6.4

6.2 6.8

3.4 7.4

To test the researcher’s hypothesis, we should use the A) paired (dependent) samples t-test. B) independent samples t-test. C) large-sample z-test. D) t-test for correlation.

59) A medical researcher wondered if there is a significant difference between the mean birth weight of boy and girl babies. A random sample of babies’ weights (pounds) showed the following: Boys Girls

8.0 5.3

4.7 2.8

7.3 6.4

6.2 6.8

3.4 7.4

How many degrees of freedom would be used to test for a zero difference in means? A) 4 B) 8 C) 10 D) must know α to say

Version 1

60) In a test of a new surgical procedure, the five most respected surgeons in FlatBroke Township were invited to Carver Hospital. Each surgeon was assigned two patients of the same age, gender, and overall health. One patient was operated upon in the old way, and the other in the new way. Both procedures are considered equally safe. The surgery times are shown below:

Old way New way

Allen

Surgeon Bob

Chloe

Daphne

Edgar

36 31

55 45

28 28

40 35

62 57

Which test should we use to test for zero difference in mean times? A) Use the paired t-test. B) Use the independent samples t-test. C) Use the independent samples z test. D) Cannot be sure which test to use without knowingα.

61) In a test of a new surgical procedure, the five most respected surgeons in FlatBroke Township were invited to Carver Hospital. Each surgeon was assigned two patients of the same age, gender, and overall health. One patient was operated upon in the old way, and the other in the new way. Both procedures are considered equally safe. The surgery times are shown below:

Old way New way

Allen

Surgeon Bob

Chloe

Daphne

Edgar

36 31

55 45

28 28

40 35

62 57

The time (in minutes) to complete each procedure was carefully recorded. In a right-tailed test for a difference of means, the test statistic is

Version 1

A) 3.162. B) 1.645. C) 1.860. D) 2.132.

62) A corporate analyst is testing whether mean inventory turnover has increased. Inventory turnover in six randomly chosen product distribution centers (PDCs) is shown.

PDC 1 PDC 2 PDC 3 PDC 4 PDC 5 PDC 6

This Year

Last Year

5.1 3.9 4.8 3.4 4.6 7.7

4.1 2.9 2.8 3.4 2.6 4.7

The degrees of freedom for the appropriate test would be A) 6. B) 5. C) 4. D) 12.

63) A corporate analyst is testing whether mean inventory turnover has increased. Inventory turnover in six randomly chosen product distribution centers (PDCs) is shown.

PDC 1 PDC 2 PDC 3 PDC 4 PDC 5 PDC 6

Version 1

This Year

Last Year

5.1 3.9 4.8 3.4 4.6 7.7

4.1 2.9 2.8 3.4 2.6 4.7

The right-tailed critical value at α = .005 is

A) 1.645. B) 1.479. C) 4.032. D) 2.015.

64) A corporate analyst is testing whether mean inventory turnover has increased. Inventory turnover in six randomly chosen product distribution centers (PDCs) is shown. This Year

Last Year

5.1 3.9 4.8 3.4 4.6 7.7

4.1 2.9 2.8 3.4 2.6 4.7

PDC 1 PDC 2 PDC 3 PDC 4 PDC 5 PDC 6

The value of the test statistic is A) 3.798. B) 2.449. C) 1.225. D) 3.503.

65) The table below shows the mean number of daily errors by seven air traffic controller trainees during the first two weeks on the job. We want to perform a paired t-test at α = .05 to see if the mean daily errors have decreased from Week 1 to Week 2.

Week 1

Version 1

5.1

3.0

Trainee T3 T4 12.1

6.2

11.5

7.8

2.2

Week 2

3.2

2.2

8.7

7.7

9.4

7.8

3.1

The right-tailed critical value at α = .05 is A) 1.895. B) 1.943. C) 2.447. D) 2.365.

66) The table below shows the mean number of daily errors by air traffic controller trainees during the first two weeks on the job. We want to perform a paired t-test at α = .05 to see if the mean daily errors decreased significantly.

Week 1 Week 2

5.1 3.2

3.0 2.2

Trainee T4 T3 12.1 8.7

6.2 7.7

11.5 9.4

7.8 7.8

2.2 3.1

The test statistic is A) 1.25. B) 1.75. C) 0.87. D) 0.79.

67) The table below shows the mean number of daily errors by air traffic controller trainees during the first two weeks on the job. We want to perform a paired t-test at α = .05 to see if the mean daily errors decreased significantly.

Week 1 Week 2

Version 1

5.1 3.2

3.0 2.2

Trainee T4 T3 12.1 8.7

6.2 7.7

11.5 9.4

7.8 7.8

2.2 3.1

What would be the degrees of freedom for the appropriate test? A) 14 B) 12 C) 7 D) 6

68)

The F-test for equality of variances assumes

A) normal populations. B) equal means. C) equal sample sizes. D) equal means and sample sizes.

69)

Which is not true of the two-tailed F-test for equality of variances?

A) It requires reversing the numerator and denominator d.f. to obtain the left-tail critical value. B) It can be avoided by "folding" the larger variance into the numerator and adjusting α. C) It is fairly robust to the presence of nonnormality in the populations being sampled. D) The null hypothesis assumes the ratio of variances equals 1.

70)

Which of the following is not a characteristic of the F distribution?

A) It is a continuous distribution. B) It is always a positive number. C) It is a family based on two sets of degrees of freedom. D) It describes the ratio of two sample means.

Version 1

71) Carver Memorial Hospital’s surgeons have a new procedure that they think will decrease the variance in the time it takes to perform an appendectomy. A sample of 8 appendectomies using the old method had a variance of 36 minutes, while a sample of 10 appendectomies using the experimental method had a variance of 16 minutes. At α = .10 in a two-tailed test for equal variances, the critical values are

A) 0.272 and 3.29. B) 0.299 and 3.07. C) 0.368 and 2.51. D) −1.645 and +1.645.

72)

The folded F-test for equality of variances

A) is rarely used because of its complexity. B) requires looking up the critical value for α/2. C) puts the smaller variance in the numerator. D) requires looking up two critical values of F instead of one.

73) An F-test for equality of variances gives a p-value of .003. At α = .05, what conclusion can be made about the preferred test to compare the means for the same sample?

A) We would prefer a pooled variance t-test for equality of means. B) We would not wish to pool the variances in a t-test for equality of means. C) We would prefer a paired t-test for equality of means. D) The variances have nothing to do with the t-test for equality of means.

Version 1

74) A random sample of Ersatz University students revealed that 16 females had a mean of $22.30 in their wallets with a standard deviation of $3.20, while 6 males had a mean of $17.30 with a standard deviation of $9.60. At α = .10, to test for equal variances in a two-tailed test, the critical values are

A) 0.441 and 3.24. B) 0.556 and 2.27. C) 0.345 and 4.62. D) 0.387 and 2.90.

75) A random sample of Ersatz University students revealed that 16 females had a mean of $22.30 in their wallets with a standard deviation of $3.20, while 6 males had a mean of $17.30 with a standard deviation of $9.60. The value of the test statistic for a folded F-test for equal variances is

A) 0.333. B) 0.111. C) 9.00. D) 3.00.

76)

Assuming unequal variances in a t-test for a zero difference of two means, we would

A) sum the degrees of freedom for each sample. B) use the larger degrees of freedom for simplicity. C) use a complicated formula for the degrees of freedom. D) use a z-test to be conservative in the calculation.

77)

The z-test for zero difference in two means

Version 1

A) is generally the preferred test for means. B) is rarely suitable for business data. C) is the most powerful test for means. D) is not available in Excel’s Data Analysis.

78)

A confidence interval for the difference of two population means

A) must pool the sample variances. B) may or may not pool the sample variances. C) cannot be used to test for equal population means. D) must have equal sample sizes.

79) A medical researcher compared the variances in birth weights for five randomly chosen babies of each gender, with the MegaStat results shown below.

F-test for equality of variance variance: Boys variance: Girls F p- value

3.537 3.288 1.08 .9453

The population variances A) may be assumed equal at any customary α. B) should be assumed unequal at any customary α. C) are not relevant to this paired t-test. D) are too small to draw a conclusion on equality or inequality.

Version 1

80) A medical researcher wondered if there is a significant difference between the mean birth weight of boy and girl babies. She weighed a random sample of five babies of each gender. Their weights (pounds) are shown below, along with some MegaStat results. Boys 5.920 1.881 5

Girls 5.740 mean 1.813 standard deviation 5n

df difference (Boys - Girls) pooled variance pooled standard deviation standard error of difference hypothesized of difference t p- value (one-tailed, upper)

8 0.1800 3.4125 1.8473 1.1683 0 0.15 .4407

The population means A) may be assumed equal at any customary α. B) should be assumed unequal at any customary α. C) are not relevant to this paired t-test. D) cannot be compared because the sample sizes are too small.

81) The coach of an adult Master's Swim class selected eight swimmers within each of the two age groups shown below. A 50-meter freestyle time is recorded for each swimmer. The resulting times (seconds) are shown below. Which statistical test would you choose to compare the two groups? Age Group Obs 1 2 3 4 5

Version 1

25 to 34 Years 26.26 28.44 26.61 29.74 26.94

35 to 44 Years 31.08 28.63 25.65 31.81 27.22

6 7 8

26.31 34.68 22.55

Mean Standard Deviation

30.56 33.38 30.82 27.69 3.50

29.89 2.54

A) t-test for independent samples with known variances. B) t-test for independent samples with unknown variances. C) t-test for paired samples. D) z-test for two independent proportions.

82) Jason wants to perform a two-tailed test for equality between two independent sample proportions. Each sample has at least 10 "successes" and 10 "failures." Jason’s test statistic is −1.44. What is his p-value?

A) .1498 B) .0749 C) .9251 D) Between .01 and .05.

83) Does the Speedo Fastskin II Male Hi-Neck Bodyskin competition racing swimsuit improve a swimmer’s 200-yard individual medley performance times? A test of 100 randomly chosen male varsity swimmers at several different universities showed that 66 enjoyed improved times, compared with only 54 of 100 female varsity swimmers. To test for equality in the proportions of men versus women who experienced improvement, the test statistic is approximately

A) 1.73. B) 1.47. C) 2.31. D) We cannot tell without knowing the tail of the test.

Version 1

84) Does the Speedo Fastskin II Male Hi-Neck Bodyskin competition racing swimsuit improve a swimmer’s 200-yard individual medley performance times? A test of 100 randomly chosen male varsity swimmers at several different universities showed that 66 enjoyed improved times, compared with only 54 of 100 female varsity swimmers. In comparing the proportions of males versus females, is it safe to assume normality?

A) Yes, clearly. B) Yes, but just barely. C) No. D) We cannot tell without knowing α.

85) The table below shows two samples taken to compare the mean age of individuals who purchased the iPhone at two AT&T store locations. Statistic Mean Standard Deviation Sample size

Ann Arbor 25.817 3.389 7

Livonia 31.248 1.874 10

What are the critical values for a two-tailed test for equal variances at α = .05? A) 0.275, 3.14 B) 0.244, 3.37 C) 0.210, 3.95 D) 0.181, 4.32

86) The table below shows two samples taken to compare the mean age of individuals who purchased the iPhone at two AT&T store locations. Statistic Mean Standard Deviation

Version 1

Ann Arbor 25.817 3.389

Livonia 31.248 1.874

Sample size

At α = .05, can you conclude that the first sample has a larger variance than the second sample? A) Yes, thep-value < .05. B) Unclear because thep-value is approximately equal to .05. C) No, thep-value > .05. D) No because thep-value is approximately equal to .05.

87) Group 1 has a mean of 13.4 and group 2 has a mean of 15.2. Both populations are known to have a variance of 9.0 and each sample consists of 18 items. What is the test statistic to test for equality of population means?

A) −1.755 B) −1.643 C) −1.800 D) −1.285

88)

Which is not a type of comparison for which you would anticipate a two-sample test?

A) Before Treatment versusAfter Treatment. B) Old Method versusNew Method. C) Sample Mean versusDesired Mean. D) Experimental Group versusControl Group.

89) Which Excel function would give the critical value for a left-tailed F test to compare two sample variances?

Version 1

A) =F.INV( α, df1,df2) B) =F.DIST( s12/ s22, df1,df2) C) =F.INV( α/2, df1,df2) D) =1−F.DIST( s12/ s22, df1,df2)

90) Which Excel function would give a p-value for a left-tailed F test to compare two sample variances? A) =1−F.DIST( s12/ s22, df1,df2) B) =F.INV( α, df1,df2) C) =F.DIST( s12/ s22, df1,df2) D) =F.INV( α/2, df1,df2)

91) The coach of a youth swim class randomly divided her 12 students into two groups. Group A students practiced using a new technique, while group B students used the old technique. After a week of training, each swimmer’s time was recorded in a 50-meter freestyle swim. Their times (in seconds) are shown below. Which statistical test would you choose to compare the two groups?

Group A 36.26 38.44 36.61 36.31 44.68 32.55

Group B 41.08 38.63 35.65 40.56 43.38 40.82

A) t-test for independent samples with known variances B) t-test for independent samples with unknown variances C) t-test for paired samples D) z-test for two independent proportions

Version 1

92) A swim academy class had eight students. After the first week of training, their times were recorded in a 50-meter freestyle swim. Times were recorded again after the second week. Which statistical test would you choose to compare the two groups? Student 1 2 3 4 5 6 7 8

Week One 26.26 28.44 26.61 29.74 26.94 26.31 34.68 22.55

Week Two 31.08 28.63 25.65 31.81 27.22 30.56 33.38 30.82

A) t-test for independent samples with known variances B) t-test for independent samples with unknown variances C) t-test for paired samples D) z-test for two independent proportions

93) The following table shows measures methane emission rates (liters/hour) from a sample of gas pipeline transfer stations. Which test would be preferred to see if emissions have decreased? Site A B C D E F G

Version 1

Last Friday 230 87 88 35 22 25 31

This Friday 233 80 77 31 19 8 36

A) Mean difference in paired samples. B) Difference of two means in independent samples. C) Either test is equivalent due to equal sample sizes. D) Difference in proportions.

94) The following table shows the number of credit cards owned by randomly chosen customers of Axolotl Bank. Which test would be preferred to compare the number of credit cards owned by individuals with only a checking account versus customer with both checking and savings accounts? Checking only Both checking and saving

0 8

12 9

6 15

10 20

13 13

17 27

22 32

5 9

A) Mean difference in paired samples. B) Difference of two means in independent samples. C) Either test is equivalent due to equal sample sizes. D) Difference in proportions.

95) A comparison of hours worked per week by randomly chosen Russian and Japanese men is shown below. Which test would be preferred to compare the means? Russian Sample mean Sample Standard Deviation Sample Size

50.06 2.435 16

Japanese 53.06 5.422 16

A) independent sample t-test for difference of two means assuming equal variances B) independent sample t-test for difference of two means assuming unequal variances C) paired t-test for mean difference due to equal sample sizes D) difference in proportions

Version 1

96)

A pooled proportion is calculated by giving each sample proportion an equal weight. ⊚ ⊚

true false

97) The difference between two sample proportions p1 − p2 may be assumed normally distributed if each sample has at least 10 "successes" and 10 "failures." ⊚ ⊚

true false

98) When testing the difference between two population proportions, it is necessary to use the same size sample from each population. ⊚ ⊚

true false

99) When using independent samples to test the difference between two population means, a pooled variance is used if the population variances are unknown and assumed equal. ⊚ ⊚

true false

100) In comparing the means of two independent samples, if the test statistic indicates a significant difference at α = .05, it will also be significant at α = .10. ⊚ ⊚

Version 1

true false

101) The degrees of freedom for the t-test used to compare two population means (independent samples) with unknown variances (assumed equal) will be n1 + n2 − 2. ⊚ ⊚

true false

102) When using independent samples to test the difference between two population means, it is desirable but not necessary for the sample sizes to be the same. ⊚ ⊚

true false

103) The Welch-Satterthwaite test is more conservative than the pooled variance test to compare two population means with unknown variances in independent samples. ⊚ ⊚

true false

104) When sample data occur in pairs, an advantage of choosing a paired t-test is that it tends to increase the power of a test, as compared to treating each sample independently. ⊚ ⊚

105)

true false

A paired t-test with two columns of 10 observations in each column would use d.f. = 18. ⊚ ⊚

true false

106) In conducting a pairedt-test mean difference, the usual null hypothesis is that the mean of the population of paired differences is zero.

Version 1

⊚ ⊚

true false

107) The t-test for two samples of paired data with n observations in each group will use n differences, making it a one-sample t-test. ⊚ ⊚

108)

The F test is used to test for the equality of two population variances. ⊚ ⊚

109)

true false

The F distribution is never negative and is always skewed right. ⊚ ⊚

true false

110) In an F test for the ratio of two population variances, the degrees of freedom in both the numerator and the denominator must be equal. ⊚ ⊚

111)

true false

The critical value in an F test for equal variances is the ratio of the sample variances. ⊚ ⊚

Version 1

true false

112)

The test statistic in an F test for equal variances is the ratio of the sample variances. ⊚ ⊚

true false

113) We could use the same data set for two independent samples (i.e., two columns of data) either to compare the means ( t-test) or to compare the variances ( F test). ⊚ ⊚

true false

114) In general, the Welch-Satterthwaite t-test for two means has the same degrees of freedom as the t-test for two means assuming equal variances. ⊚ ⊚

true false

115) When the variances are known, a test comparing two independent sample means would use the normal distribution. ⊚ ⊚

true false

116) When the variances are unknown, a test comparing two independent sample means would use the Student’s t distribution. ⊚ ⊚

true false

117) If the sample proportions are p1 = 15/60 and p2 = 20/90, normality may be assumed in a test comparing the two population proportions.

Version 1

⊚ ⊚

true false

118) If the sample proportions are p1 = 6/90 and p2 = 4/100, normality may be assumed in a test comparing the two population proportions. ⊚ ⊚

119)

A paired t-test with two columns of eight observations in each column would use d.f. = 7. ⊚ ⊚

120)

true false

If the population variances are exactly equal, the sample F test statistic will be zero. ⊚ ⊚

121)

true false

Two-sample hypothesis tests compare differences or ratios to hypothesized values. ⊚ ⊚

true false

122) Sample statistics drawn from two populations that have the same parameter will be identical. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 10_7e_Doane 1) B 2) A 3) C 4) B 5) B 6) D 7) C 8) C 9) A 10) B 11) A 12) D 13) B 14) B 15) A 16) C 17) C 18) B 19) A 20) C 21) C 22) D 23) B 24) C 25) C 26) B Version 1

27) B 28) D 29) B 30) B 31) B 32) A 33) C 34) B 35) C 36) B 37) C 38) A 39) D 40) C 41) B 42) D 43) A 44) A 45) B 46) D 47) B 48) D 49) B 50) C 51) B 52) D 53) A 54) D 55) A 56) A Version 1

57) A 58) B 59) B 60) A 61) A 62) B 63) C 64) D 65) B 66) A 67) D 68) A 69) C 70) D 71) A 72) B 73) B 74) C 75) C 76) C 77) B 78) B 79) A 80) A 81) B 82) A 83) A 84) A 85) D 86) A Version 1

87) C 88) C 89) A 90) C 91) B 92) C 93) A 94) B 95) B 96) FALSE 97) TRUE 98) FALSE 99) TRUE 100) TRUE 101) TRUE 102) TRUE 103) TRUE 104) TRUE 105) FALSE 106) TRUE 107) TRUE 108) TRUE 109) TRUE 110) FALSE 111) FALSE 112) TRUE 113) TRUE 114) FALSE 115) TRUE 116) TRUE Version 1

117) TRUE 118) FALSE 119) TRUE 120) FALSE 121) TRUE 122) FALSE

Version 1

CHAPTER 11 1)

Which is the Excel function to find the critical value of F for α = .05, df1 = 3, df2 = 25?

A) =F.DIST(.05, 2, 24) B) =F.INV.RT(.05, 3, 25) C) =F.DIST(.05, 3, 25) D) =F.INV(.05, 2, 24)

2) Which Excel function gives the right-tail p-value for an ANOVA test with a test statistic Fcalc = 4.52, n = 29 observations, and c = 4 groups?

A) =F.DIST.RT(4.52, 3, 25) B) =F.INV(4.52, 4, 28) C) =F.DIST(4.52, 4, 28) D) =F.INV(4.52, 3, 25)

Variation "within" the ANOVA treatments represents

A) random variation. B) differences between group means. C) differences between group variances. D) the effect of sample size.

Variation "between" the ANOVA treatments represents

Version 1

A) random variation. B) differences between group means. C) differences between group variances. D) the effect of sample size.

Which is not an assumption of ANOVA?

A) normality of the treatment populations B) homogeneous treatment variances C) independent sample observations D) equal population sizes for groups

Which is a necessary assumption of ANOVA?

A) nonnormality of the treatment populations B) different treatment variances C) independent sample observations D) unequal population sizes for groups

In an ANOVA, when would the F-test statistic be zero?

A) when there is no difference in the variances B) when the treatment means are the same C) when the observations are normally distributed D) the F-test statistic cannot ever be zero.

ANOVA is used to compare

Version 1

A) proportions of several groups. B) variances of several groups. C) means of several groups. D) both means and variances.

Analysis of variance is a technique used to test for

A) equality of two or more variances. B) equality of two or more means. C) equality of a population mean and a given value. D) equality of more than two variances.

10)

Which of the following is not a characteristic of the F distribution?

A) It is always right-skewed. B) It describes the ratio of two variances. C) It is a family based on two sets of degrees of freedom. D) It is negative when s12 is smaller than s22.

11)

Which of the following is a characteristic of theF distribution?

A) It can be either left- or right-skewed. B) It describes the ratio of two variances. C) The degrees of freedom is based on the larger sample size. D) It is always negative when s12 is smaller than s22.

12)

In an ANOVA, the SSE (error) sum of squares reflects

Version 1

A) the effect of the combined factor(s). B) the overall variation in Y that is to be explained. C) the variation that is not explained by the factors. D) the combined effect of treatments and sample size.

13) To test the null hypothesis H0: μ1 = μ2 = μ3 using samples from normal populations with unknown but equal variances, we

A) cannot safely use ANOVA. B) can safely employ ANOVA. C) would prefer three separate t-tests. D) would need three-factor ANOVA.

14)

Which is not assumed in ANOVA?

A) Observations are independent. B) Populations are normally distributed. C) Variances of all treatment groups are the same. D) Population variances are known.

15)

In a one-factor ANOVA, the computed value of F will be negative

A) when there is no difference in the treatment means. B) when there is no difference within the treatments. C) when the SST (total) is larger than SSE (error). D) under no circumstances.

Version 1

16) Degrees of freedom for the between-group variation in a one-factor ANOVA with n1 = 5, n2 = 6, n3 = 7 would be

A) 18. B) 17. C) 6. D) 2.

17) Degrees of freedom for the between-group variation in a one-factor ANOVA with n1 = 8, n2 = 5, n3 = 7, n4 = 9 would be

A) 28. B) 3. C) 29. D) 4.

18) Using one-factor ANOVA with 30 observations, we find at α = .05 that we cannot reject the null hypothesis of equal means. We increase the sample size from 30 observations to 60 observations and obtain the same value for the sample F-test statistic. Which is correct?

A) We might now be able to reject the null hypothesis. B) We surely must reject H0 for 60 observations C) We cannot reject H0 since we obtained the same F-value. D) It is impossible to get the same F-value for n = 60 as for n = 30.

19)

One-factor analysis of variance

Version 1

A) requires that the number of observations in each group be identical. B) has less power when the number of observations per group is not identical. C) is extremely sensitive to slight departures from normality. D) is a generalization of the t-test for paired observations.

20)

In a one-factor ANOVA, the total sum of squares is equal to

A) the sum of squares within groups plus the sum of squares between groups. B) the sum of squares within groups times the sum of squares between groups. C) the sum of squares within groups divided by the sum of squares between groups. D) the means of all the groups squared.

21)

The within-treatment variation reflects

A) variation among individuals of different groups. B) variation between individuals in different groups. C) variation explained by factors included in the ANOVA model. D) variation that is not part of the ANOVA model.

22)

Given the following ANOVA table (some information is missing), find the F statistic.

Source Treatment

Sum of Squares 744.00

Mean Square 4

Error

751.50

Total

1,495.50

Version 1

A) 3.71 B) 0.99 C) 0.497 D) 4.02

23) Given the following ANOVA table (some information is missing), find the critical value of F.05. Source

Sum of Squares

Treatment

744.00

Error

751.50

Total

1,495.50

Mean Square

F.05

A) 3.06 B) 2.90 C) 2.36 D) 3.41

24) Identify the degrees of freedom for the treatment and error in this one-factor ANOVA (blanks indicate missing information). Source Treatment

Sum of Squares 993

Error

1,002

Total

1,995

Mean Square 331.0 50.1

A) 4, 24 B) 3, 20 C) 5, 23 D) 5, 20

Version 1

25) For this one-factor ANOVA (some information is missing), how many treatment groups were there? Source Treatment

Sum of Squares 654

Error

3,456

Total

4,110

Mean Square 218

128

A) cannot be determined B) 3 C) 4 D) 2

26)

For this one-factor ANOVA (some information is missing), what is the F-test statistic?

Source Treatment

Sum of Squares 654

Error

3,456

Total

4,110

Mean Square 218

128

A) 0.159 B) 2.833 C) 1.703 D) cannot be determined

27)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups

Version 1

MS F 210.2788

1483

Within groups Total

74.15

2113.833

TheF-test statistic is

A) 2.84. B) 3.56. C) 2.80. D) 2.79.

28)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups

Within groups Total

1483

MS 210.2778

74.15

2113.833

Degrees of freedom for between-groups variation are A) 3. B) 4. C) 5. D) We cannot tell from given information.

29)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups Within groups

Version 1

1483

MS 210.2778

74.15

2113.833

Total

SS for between-groups variation will be A) 129.99. B) 630.83. C) 1233.4. D) We cannot tell from given information.

30)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups

Within groups Total

1483

MS 210.2778

74.15

2113.833

The number of treatment groups is A) 4. B) 3. C) 2. D) 1.

31)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups Within groups Total

Version 1

1483

MS 210.2778

74.15

2113.833

The sample size is A) 20. B) 23. C) 24. D) 21.

32)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups

Within groups Total

1483

MS 210.2778

74.15

2113.833

Assuming equal group sizes, the number of observations in each group is A) 2. B) 3. C) 4. D) 6.

33)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups Within groups Total

1483

MS 210.2778

74.15

2113.833

Degrees of freedom for the F-test are

Version 1

A) 5, 22. B) 4, 21. C) 3, 20. D) impossible to determine.

34)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups

Within groups

1483

Total

210.2778

P-value

F crit

0.064139

74.15

2113.833

The critical value of F at α = .05 is A) 1.645. B) 2.84. C) 3.10. D) 4.28.

35)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Between groups Within groups Total

1483

MS 210.2778

P-value 0.064139

74.15

2113.833

At α = .05, the difference between group means is

Version 1

A) highly significant. B) barely significant. C) not quite significant. D) clearly insignificant.

36) The Internal Revenue Service wishes to study the time required to process tax returns in three regional centers. A random sample of three tax returns is chosen from each of three centers. The time (in days) required to process each return is recorded as shown below. East 49 39 45

West 47 52 51

Midwest 54 49 56

The test to use to compare the means for all three groups would require A) three-factor ANOVA. B) one-factor ANOVA. C) repeated two-sample test of means. D) two-factor ANOVA with replication.

37) The Internal Revenue Service wishes to study the time required to process tax returns in three regional centers. A random sample of three tax returns is chosen from each of three centers. The time (in days) required to process each return is recorded as shown below. Subsequently, an ANOVA test was performed. East 49 39 45

West 47 52 51

Midwest 54 49 56

Degrees of freedom for the error sum of squares in the ANOVA would be

Version 1

A) 11. B) 2. C) 4. D) 6.

38) The Internal Revenue Service wishes to study the time required to process tax returns in three regional centers. A random sample of three tax returns is chosen from each of three centers. The time (in days) required to process each return is recorded as shown below. East 49 39 45

West 47 52 51

Midwest 54 49 56

Degrees of freedom for the between-groups sum of squares in the ANOVA would be A) 11. B) 2. C) 4. D) 6.

39) Professor Gristmill sampled exam scores for five randomly chosen students from each of his two sections of ACC 200. His sample results are shown. Day Class Night Class

93 91

58 81

74 85

85 60

82 73

He could test the population means for equality using A) a t-test for two means from independent samples. B) a t-test for two means from paired (related) samples. C) a one-factor ANOVA. D) either a one-factor ANOVA or a two-tailed t-test.

Version 1

Systolic blood pressure of randomly selected HMO patients was recorded on a particular 40) Wednesday, with the results shown here:

Under 20 105 113 108 114 123

Patient Age Group 20 to 29 30 to 49 110 122 101 114 112 128 127 124 123 125

50 and Over 139 115 136 124 123

The appropriate hypothesis test is A) one-factor ANOVA. B) two-factor ANOVA. C) three-factor ANOVA. D) four-factor ANOVA.

41) Systolic blood pressure of randomly selected HMO patients was recorded on a particular Wednesday, with the results shown here. An ANOVA test was performed using these data.

Under 20 105 113 108 114 123

Patient Age Group 20 to 29 30 to 49 110 122 101 114 112 128 127 124 123 125

50 and Over 139 115 136 124 123

Degrees of freedom for the between-treatments sum of squares would be A) 3. B) 19. C) 17. D) It depends on α.

Version 1

Systolic blood pressure of randomly selected HMO patients was recorded on a particular 42) Wednesday, with the results shown here. An ANOVA test was performed using these data.

Under 20 105 113 108 114 123

Patient Age Group 20 to 29 30 to 49 110 122 101 114 112 128 127 124 123 125

50 and Over 139 115 136 124 123

What are the degrees of freedom for the error sum of squares? A) 3 B) 19 C) 16 D) It depends on α.

43) Sound levels are measured at random moments under typical driving conditions for various full-size truck models. The Excel ANOVA results are shown below. Mean Big Bruin Gran Conto MaxRanger Oso Grande Overall Source Between Within Total

SS 462.4 934.70 1,397.10

57.44 56.50 64.51 54.15 57.73 d.f 3 27 30

Standard Deviation 8.944 6.361 3.983 4.166 6.824 MS 154.1 34.6

n 6 8 7 10 31

The test statistic to compare the five means simultaneously is

Version 1

A) 2.96. B) 15.8. C) 5.56. D) 4.45.

44) Sound levels are measured at random moments under typical driving conditions for various full-size truck models. The ANOVA results are shown below. Mean Big Bruin Gran Conto MaxRanger Oso Grande Overall Source Between Within Total

SS 462.4 934.70 1,397.10

57.44 56.50 64.51 54.15 57.73 d.f 3 27 30

Standard Deviation 8.944 6.361 3.983 4.166 6.824 MS 154.1 34.6

n 6 8 7 10 31

The test statistic for Hartley’s test for homogeneity of variance is A) 2.25. B) 5.04. C) 4.61. D) 4.45.

45)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA Table Source Treatment

Version 1

SS 44,757

MS 11,189

Error

89,025

Total

133,782

1,619

The number of treatment groups is A) 5. B) 4. C) 3. D) impossible to ascertain from given information.

46)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA Table Source Treatment

SS 44,757

MS 11,189

Error

89,025

1,619

Total

133,782

The F statistic is A) 2.88. B) 4.87. C) 5.93. D) 6.91.

47)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA Table Source Treatment

Version 1

SS 44,757

MS 11,189

Error

89,025

Total

133,782

1,619

The number of observations in the original sample was A) 59. B) 60. C) 58. D) 54.

48)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA Table Source Treatment

SS 44,757

MS 11,189

Error

89,025

1,619

Total

133,782

Using Appendix F, the 5 percent critical value for the F-test is approximately A) 3.24. B) 6.91. C) 2.56. D) 2.06.

49)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA Table Source Treatment

Version 1

SS 44,757

MS 11,189

Error

89,025

Total

133,782

1,619

The p-value for the F-test would be A) much less than .05. B) slightly less than .05. C) slightly greater than .05. D) much greater than .05.

50)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA Table Source Treatment

SS 717.4

df 3

Error

P-value .0442

70.675

Total

1848.2

The MS (mean square) for the treatments is A) 239.13. B) 106.88. C) 1,130.8. D) impossible to ascertain from the information given.

51)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA table Source Treatment

Version 1

SS 717.4

df 3

P-value .0442

70.675

Error 1848.2

Total

The F statistic is A) 4.87. B) 3.38. C) 5.93. D) 6.91.

52)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA table Source Treatment

SS 717.4

df 3

Error

P-value .0442

70.675

Total

1848.2

The number of observations in the entire sample is A) 20. B) 19. C) 22. D) 18.

53)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA table Source Treatment

Version 1

SS 717.4

df 3

P-value .0442

70.675

Error 1848.2

Total

The 5 percent critical value for the F test is A) 2.46. B) 3.24. C) 3.38. D) impossible to ascertain from the given information.

54)

Refer to the following partial ANOVA results from Excel (some information is missing).

ANOVA table Source Treatment

SS 717.40

df 3

Error

P-value .0442

70.675

Total

1848.20

Our decision about the hypothesis of equal treatment means is that the null hypothesis A) cannot be rejected at α = .05. B) can be rejected at α = .05. C) can be rejected for any typical value of α. D) cannot be assessed from the given information.

55) To compare the cost of three shipping methods, a random sample of four shipments is taken for each of three firms. The cost per shipment is shown below. SpeedyShip GetItThere WeRTops

Version 1

355 342 361

435 441 430

422 402 435

518 488 528

In a one-factor ANOVA, the degrees of freedom for the between-groups sum of squares will be A) 11. B) 3. C) 2. D) 9.

56) To compare the cost of three shipping methods, a random sample of four shipments is taken for each of three firms. The cost per shipment is shown below. SpeedyShip GetItThere WeRTops

355 342 361

435 441 430

422 402 435

518 488 528

In a one-factor ANOVA, the degrees of freedom for the within-groups sum of squares will be A) 11. B) 3. C) 9. D) 2.

57) To compare the cost of three shipping methods, a random sample of four shipments is taken for each of three firms. The cost per shipment is shown below. SpeedyShip GetItThere WeRTops

355 342 361

435 441 430

422 402 435

518 488 528

The degrees of freedom for the total sum of squares in a one-factor ANOVA would be

Version 1

A) 11. B) 8. C) 2. D) 9.

58) Refer to the following MegaStat output (some information is missing). The sample size was n = 65 in a one-factor ANOVA. Tukey simultaneous comparison t-values Monday

Friday

Tuesday

Thursday

Wednesday

Monday Friday

3.02

Tuesday

3.08

0.07

Thursday

4.46

1.45

1.38

Wednesday

4.64

1.62

1.55

0.17

At α = .05, which is the critical value of the test statistic for a two-tailed test for a significant difference in means that are to be compared simultaneously? Note: This question requires a Tukey table. A) 2.81 B) 2.54 C) 2.33 D) 1.96

59) Refer to the following MegaStat output (some information is missing). The sample size was n = 65 in a one-factor ANOVA.

Version 1

Tukey simultaneous comparison t-values Monday

Friday

Tuesday

Thursday

Wednesday

Monday Friday

3.02

Tuesday

3.08

0.07

Thursday

4.46

1.45

1.38

Wednesday

4.64

1.62

1.55

0.17

Which pairs of days differ significantly? Note: This question requires access to a Tukey table. A) (Monday, Thursday) and (Monday, Wednesday) only B) (Monday, Wednesday) only C) (Monday, Thursday) only D) (Monday, Thursday) and (Monday, Wednesday) and (Monday, Friday) and (Monday, Tuesday)

60) Refer to the following MegaStat output (some information is missing). The sample size was n = 24 in a one-factor ANOVA. Tukey simultaneous comparison t-values Med 4 Med 1 Med 3

Med 2

Med 4 Med 1

1.78

Med 3

2.01

0.24

Med 2

2.84

1.07

0.83

At α = .05, what is the critical value of the Tukey test statistic for a two-tailed test for a significant difference in means that are to be compared simultaneously? Note: This question requires access to a Tukey table.

Version 1

A) 2.07 B) 2.80 C) 2.76 D) 1.96

61) Refer to the following MegaStat output (some information is missing). The sample size was n = 24 in a one-factor ANOVA. Tukey simultaneous comparison t-values Med 4 Med 1 Med 3

Med 2

Med 4 Med 1

1.78

Med 3

2.01

0.24

Med 2

2.84

1.07

0.83

Which pairs of meds differ at α = .05? Note: This question requires access to a Tukey table. A) Med 1, Med 2 B) Med 2, Med 4 C) Med 3, Med 4 D) None of the answers are correct.

What is the .05 critical value of Hartley’s test statistic for a one-factor ANOVA with n1 = 62) 5, n2 = 8, n3 = 7, n4 = 8, n5 = 6, n6 = 8? Note: This question requires access to a Hartley table.

A) 10.8 B) 11.8 C) 13.7 D) 15.0

Version 1

What is the .05 critical value of Tukey’s test statistic for a one-factor ANOVA with n1 = 63) 6, n2 = 6, n3 = 6? Note: This question requires access to a Tukey table.

A) 3.67 B) 2.60 C) 3.58 D) 2.75

64) What are the degrees of freedom for Hartley’s test statistic for a one-factor ANOVA with n1 = 5, n2 = 8, n3 = 7, n4 = 8, n5 = 6, n6 = 8?

A) 7, 6 B) 6, 6 C) 6, 41

65) What are the degrees of freedom for Tukey’s test statistic for a one-factor ANOVA with n1 = 6, n2 = 6, n3 = 6?

A) 3, 6 B) 6, 3 C) 6, 15 D) 3, 15

66) After performing a one-factor ANOVA test, John noticed that the sample standard deviations for his four groups were, respectively, 33, 24, 79, and 35. John should

Version 1

A) feel confident in his ANOVA test. B) use Hartley’s test to check his assumptions. C) use an independent samples t-test instead of ANOVA. D) use a paired t-test instead of ANOVA.

67)

Which statement is incorrect?

A) We need a Tukey test because ANOVA does not tell which pairs of means differ. B) Hartley’s test is needed to determine whether the means of the groups differ. C) ANOVA assumes equal variances in the c groups being compared. D) ANOVA assumes populations are normally distributed.

68)

Which statement iscorrect?

A) We need a Tukey test because ANOVA does not tell which pairs of means differ. B) Hartley's test is needed to determine whether the means of the groups differ. C) ANOVA does not assume equal variances in thec groups being compared. D) ANOVA does not assume populations are normally distributed.

69)

Which is not an assumption of unreplicated two-factor ANOVA (randomized block)?

A) normality of the population B) homogeneous variances C) additive treatment effects D) there is factor interaction

70)

Which is correct concerning a two-factor unreplicated (randomized block) ANOVA?

Version 1

A) No interaction effect is estimated. B) The interaction effect would have its own F statistic. C) The interaction would be insignificant unless the main effects were significant. D) There is a within sample variance estimated.

71)

Which isincorrect concerning a two-factor unreplicated (randomized block) ANOVA?

A) No interaction effect is estimated. B) Row and column effects would have their ownF statistic. C) The interaction would be insignificant unless the main effects were significant. D) There is a no within sample variance estimated.

72) In a two-factor unreplicated (randomized block) ANOVA, what is the F statistic for the treatment effect given that SSA (treatments) = 216, SSB (block) = 126, SSE (error) = 18?

A) 12 B) 1.71 C) 7 D) We cannot tell without more information.

73) Three bottles of wine are tasted by three experts. Each rater assigns a rating (scale is from 1=terrible to 10=superb). Which test would you use for the most obvious hypothesis?

Bob Fritz Sasha

Version 1

Wine 1

Wine 2

Wine 3

9 9 8

8 7 8

7 8 6

A) t-test for independent means B) one-factor ANOVA C) two-factor ANOVA without replication D) two-factor ANOVA with replication

74) To compare the cost of three shipping methods, a firm ships material to each of four different destinations over a six-month period. The average cost per shipment is shown below.

Shipper SpeedyShip GetItThere WeRTops

Destination Toledo Oshawa 355 435 342 441 361 430

Janesville 422 402 435

Dallas 518 488 528

Which test would be appropriate? A) independent samples t-test B) two-factor ANOVA with replication C) dependent (paired-samples) t-test D) two-factor ANOVA without replication

75) To compare the cost of three shipping methods, a firm ships material to each of four different destinations over a six-month period. The average cost per shipment is shown below.

Shipper SpeedyShip GetItThere WeRTops

Destination Toledo Oshawa 355 435 342 441 361 430

Janesville 422 402 435

Dallas 518 488 528

For the appropriate type of ANOVA, total degrees of freedom would be

Version 1

A) 11. B) 3. C) 4. D) 12.

76) Here is an Excel ANOVA table that summarizes the results of an experiment to assess the effects of ambient noise level and plant location on worker productivity. The test used α = .05. Source of Variation Plant location Noise level Error

P-value

F crit

3.0075 8.4075 3.5225

3 3 9

1.0025 2.8025 0.3914

2.561 7.160

0.1199 0.0093

3.862 3.863

Total

14.9375

Is the effect of plant location significant at α = .05? A) yes B) no C) need more information to say D) only if one were to conclude that Noise level is significant

77) Here is an Excel ANOVA table that summarizes the results of an experiment to assess the effects of ambient noise level and plant location on worker productivity. The test used α = .05. Source of Variation Plant location Noise level Error

P-value

F crit

3.0075 8.4075 3.5225

3 3 9

1.0025 2.8025 0.3914

2.561 7.160

0.1199 0.0093

3.862 3.863

Total

14.9375

Version 1

Is the effect of noise level significant at α = .05? A) yes B) no C) we need more information to say D) only if we were to conclude that Plant location were significant

78) Here is an Excel ANOVA table that summarizes the results of an experiment to assess the effects of ambient noise level and plant location on worker productivity. The test used α = .05. Source of Variation Plant location Noise level Error

P-value

F crit

3.0075 8.4075 3.5225

3 3 9

1.0025 2.8025 0.3914

2.561 7.160

0.1199 0.0093

3.862 3.863

Total

14.9375

The experimental design and ANOVA appear to be A) replicated two factor. B) unreplicated two-factor. C) impossible to determine. D) randomized three-factor ANOVA.

79) Here is an Excel ANOVA table that summarizes the results of an experiment to assess the effects of ambient noise level and plant location on worker productivity. The test used α = .05. Source of Variation Plant location Noise level Error

Version 1

P-value

F crit

3.0075 8.4075 3.5225

3 3 9

1.0025 2.8025 0.3914

2.561 7.160

0.1199 0.0093

3.862 3.863

Total

14.9375

The sample size is A) 15. B) 10. C) 16. D) impossible to determine.

80) At the Seymour Clinic, the number of patients seen by three doctors over five days is as follows:

Day Monday Tuesday Wednesday Thursday Friday

Physician Doctor Able 19 20 22 19 20

Br. Baker 25 22 24 20 34

Doctor Chow 27 27 32 22 27

This data set would call for A) two-factor ANOVA without replication. B) two-factor ANOVA with replication. C) three-factor ANOVA. D) five-factor ANOVA.

81) At the Seymour Clinic, the number of patients seen by three doctors over five days is as follows:

Day Monday Tuesday

Version 1

Physician Doctor Able 19 20

Br. Baker 25 22

Doctor Chow 27 27

Wednesday Thursday Friday

22 19 20

24 20 34

32 22 27

Degrees of freedom for the error sum of squares would be A) 6. B) 14. C) 8. D) 15.

82) Here is an Excel ANOVA table for an experiment that analyzed factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type Patient age group

SS 16.5313 25.0938

df 1

MS 16.5313 8.3646

F 9.173 4.642

P-value 0.006 0.011

Interaction Error

1.8438 43.2504

3 24

0.6146 1.8021

0.341

0.796

Total

86.7192

The number of medication types is A) 1. B) 2. C) 3. D) 4.

83) Here is an Excel ANOVA table for an experiment that analyzed two factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type

Version 1

SS 16.5313

df 1

MS 16.5313

F 9.173

P-value 0.006

Patient age group

25.0938

Interaction Error

1.8438 43.2504

Total

86.7192

3 24

8.3646

4.642

0.011

0.6146 1.8021

0.341

0.796

The number of patient age groups is A) 1. B) 2. C) 3. D) 4.

84) Here is an Excel ANOVA table for an experiment that analyzed two factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type Patient age group

SS 16.5313 25.0938

df 1

MS 16.5313 8.3646

F 9.173 4.642

P-value 0.006 0.011

Interaction Error

1.8438 43.2504

3 24

0.6146 1.8021

0.341

0.796

Total

86.7192

The number of patients per replication is A) 1. B) 2. C) 3. D) 4.

Version 1

85) Here is an Excel ANOVA table for an experiment that analyzed two factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type Patient age group

SS 16.5313 25.0938

df 1

MS 16.5313 8.3646

F 9.173 4.642

P-value 0.006 0.011

Interaction Error

1.8438 43.2504

3 24

0.6146 1.8021

0.341

0.796

Total

86.7192

The overall sample size is A) 7. B) 25. C) 32. D) impossible to determine as given.

86) Here is an Excel ANOVA table for an experiment that analyzed two factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type Patient age group

SS 16.5313 25.0938

df 1

MS 16.5313 8.3646

F 9.173 4.642

P-value 0.006 0.011

Interaction Error

1.8438 43.2504

3 24

0.6146 1.8021

0.341

0.796

Total

86.7192

At α = .05 the effect of medication type is A) significant. B) insignificant. C) borderline.

Version 1

87) Here is an Excel ANOVA table for an experiment that analyzed two factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type Patient age group

SS 16.5313 25.0938

df 1

MS 16.5313 8.3646

F 9.173 4.642

P-value 0.006 0.011

Interaction Error

1.8438 43.2504

3 24

0.6146 1.8021

0.341

0.796

Total

86.7192

At α = .01 the effect of patient age is A) very clearly significant. B) just barely significant. C) not quite significant.

88) Here is an Excel ANOVA table for an experiment that analyzed two factors that may affect patients’ blood pressure (some information is missing). Source of Variation Medication type Patient age group

SS 16.5313 25.0938

df 1

MS 16.5313 8.3646

F 9.173 4.642

P-value 0.006 0.011

Interaction Error

1.8438 43.2504

3 24

0.6146 1.8021

0.341

0.796

Total

86.7192

At α = .05 the interaction is

Version 1

A) significant. B) insignificant. C) borderline.

89) Three randomly chosen pieces of four types of polyvinyl chloride (PVC) pipe of equal wall thickness are tested to determine the burst strength (in pounds per square inch) under three temperature conditions, yielding the results shown below. Temperature

PVC1 250

PVC2 301

PVC3 235

PVC4 217

Hot (70° C)

273 281

285 275

260 279

255 241

321

342

302

240

322 299

322 339

315 301

260 278

358

375

328

301

363 341

355 354

336 342

333 302

Warm (40° C)

Cold (10° C)

Which test would be appropriate? A) one-factor ANOVA B) two-factor ANOVA with replication C) dependent (paired-samples)t-test D) two-factor ANOVA with no replication

90) Three randomly chosen pieces of four types of PVC pipe of equal wall thickness are tested to determine the burst strength (in pounds per square inch) under three temperature conditions, yielding the results shown below.

Version 1

Temperature

PVC1 250

PVC2 301

PVC3 235

PVC4 217

Hot (70° C)

273 281

285 275

260 279

255 241

321

342

302

240

322 299

322 339

315 301

260 278

358

375

328

301

363 341

355 354

336 342

333 302

Warm (40° C)

Cold (10° C)

Total degrees of freedom for the ANOVA would be A) 19. B) 12. C) 35. D) 59.

91) A firm is studying the effect of work shift and parts supplier on its defect rate (dependent variable is defects per 1000). The resulting ANOVA results are shown below (some information is missing). Source

Shift Supplier

Sum of Squares 704.07 19.6

Shift*Supplier Error

430.75 1062.05

4 36

Total

2216.47

Mean Square 352.04 9.8 107.69 29.5

P-Value

11.93 0.33

0.001 0.72

3.65

0.014

How many suppliers were there?

Version 1

A) 1 B) 2 C) 3 D) 4

92) A firm is studying the effect of work shift and parts supplier on its defect rate (dependent variable is defects per 1000). The resulting ANOVA results are shown below (some information is missing). Source

Shift Supplier

Sum of Squares 704.07 19.6

Shift*Supplier Error

430.75 1062.05

4 36

Total

2216.47

Mean Square 352.04 9.8 107.69 29.5

P-Value

11.93 0.33

0.001 0.72

3.65

0.014

How many replications per cell were there? A) 2 B) 3 C) 4 D) 5

93) A firm is studying the effect of work shift and parts supplier on its defect rate (dependent variable is defects per 1000). The resulting ANOVA results are shown below (some information is missing). Source Shift Supplier

Version 1

Sum of Squares 704.07 19.6

df 2

Mean Square 352.04 9.8

P-Value

11.93 0.33

0.001 0.72

Shift*Supplier Error

430.75 1062.05

4 36

Total

2216.47

107.69 29.5

3.65

0.014

At α = .05, the effect of supplier is A) clearly significant. B) just barely significant. C) almost but not quite significant. D) clearly insignificant.

94) A firm is studying the effect of work shift and parts supplier on its defect rate (dependent variable is defects per 1000). The resulting ANOVA results are shown below (some information is missing). Source

Shift Supplier

Sum of Squares 704.07 19.6

Shift*Supplier Error

430.75 1062.05

4 36

Total

2216.47

Mean Square 352.04 9.8 107.69 29.5

P-Value

11.93 0.33

0.001 0.72

3.65

0.014

The number of observations was A) 37. B) 45. C) 44. D) 40.

Version 1

95) A firm is studying the effect of work shift and parts supplier on its defect rate (dependent variable is defects per 1000). The resulting ANOVA results are shown below (some information is missing). Source

Shift Supplier

Sum of Squares 704.07 19.6

Shift*Supplier Error

430.75 1062.05

4 36

Total

2216.47

Mean Square 352.04 9.8 107.69 29.5

P-Value

11.93 0.33

0.001 0.72

3.65

0.014

At α = .01, the interaction effect is A) strongly significant. B) just barely significant. C) not quite significant. D) undoubtably insignificant.

96) A firm is concerned with variability in hourly output at several factories and shifts. Here are the results of an ANOVA using output per hour as the dependent variable (some information is missing). Source Factory Supplier Factory*Shift Error Total

Sum of Squares 19012.5 258.333 80908.333 8633.333

df 1 2 2 12

Mean Square 19012.5 129.167 40454.167 719.444

108812.5

6400.735

F Ratio 26.427 0.180 56.230

The original data matrix has how many treatments (rows × columns)?

Version 1

A) 4 B) 6 C) 3 D) 8

97) A firm is concerned with variability in hourly output at several factories and shifts. Here are the results of an ANOVA using output per hour as the dependent variable (some information is missing). Source Factory Supplier Factory*Shift Error

Sum of Squares 19012.5 258.333 80908.333 8633.333

df 1 2 2 12

Mean Square 19012.5 129.167 40454.167 719.444

108812.5

6400.735

Total

F Ratio 26.427 0.180 56.230

The number of observations in each treatment cell (row-column intersection) is

A) 1. B) 2. C) 3. D) impossible to determine.

98) A firm is concerned with variability in hourly output at several factories and shifts. Here are the results of an ANOVA using output per hour as the dependent variable (some information is missing). Source Factory Supplier Factory*Shift Error

Version 1

Sum of Squares 19012.5 258.333 80908.333 8633.333

df 1 2 2 12

Mean Square 19012.5 129.167 40454.167

F Ratio 26.427 0.180 56.230

P-value 0.000 0.838

719.444

Total

108812.5

6400.735

Atα = .01 the effect of factory is

A) clearly significant. B) clearly insignificant. C) of borderline significance. D) barely insignificant.

99) A firm is concerned with variability in hourly output at several factories and shifts. Here are the results of an ANOVA using output per hour as the dependent variable (some information is missing). Source Factory Supplier Factory*Shift

Sum of Squares 19012.5 258.333 80908.333

df 1 2 2

Mean Square 19012.5 129.167 40454.167

Error

8633.333

719.444

Total

108812.5

6400.735

F Ratio 26.427 0.180 56.230

P-value 0.000 0.838

The p-value for the interaction effect is going to be

A) very small (near 0). B) very large (near 1). C) impossible to know—could be either large or small. D) close to 0.10.

100) Sound engineers studied factors that might affect the output (in decibels) of a rock concert speaker system. The results of their ANOVA tests are shown (some information is missing).

Version 1

Source of Variation Amplifier

SS 99.02344

Position

93.98698

Interaction Error

10.15365 155.875

3 16

Total

359.0391

MS 99.02344

P-value 0.005718

31.32899

3.215807

0.051003

3.384549 9.742188

0.347412

0.791505

Which is the number of amplifiers and positions tested?

A) 1, 3 B) 2, 4 C) 3, 5 D) 4, 1

101) Sound engineers studied factors that might affect the output (in decibels) of a rock concert speaker system. The results of their ANOVA tests are shown (some information is missing). Source of Variation Amplifier

SS 99.02344

Position

93.98698

Interaction Error

10.15365 155.875

3 16

Total

359.0391

MS 99.02344

31.32899

3.215807

3.384549 9.742188

0.347412

The number of observations per cell was

Version 1

A) 1. B) 2. C) 3. D) 4.

102) Sound engineers studied factors that might affect the output (in decibels) of a rock concert speaker system. The desired level of significance was α = .05. The results of their ANOVA tests are shown (some information is missing). Source of Variation Amplifier

SS 99.02344

Position

93.98698

Interaction Error

10.15365 155.875

3 16

Total

359.0391

MS 99.02344

P-value 0.005718

31.32899

3.215807

0.051003

3.384549 9.742188

0.347412

0.791505

Themost reasonable conclusion atα = .05 about the three sources of variation (amplifier, position, and interaction) would be that their effects are

A) significant, significant, insignificant. B) insignificant, significant, significant. C) very significant, almost significant, insignificant. D) insignificant, insignificant, insignificant.

103) Sound engineers studied factors that might affect the output, in decibels, of a rock concert speaker system. The results of their ANOVA tests are shown (some information is missing). Source of Variation Amplifier

SS 99.02344

Position

93.98698

Interaction

10.15365

Version 1

MS 99.02344

31.32899

3.215807

3.384549

0.347412

Error

155.875

Total

359.0391

9.742188

TheF statistic for amplifier was

A) 9.90. B) 10.16. C) 5.72. D) 4.27.

104) A multinational firm manufactures several types of 1280 × 1024 LCD displays in several locations. They designed a sampling experiment to analyze the number of pixels per screen that have significant color degradation after 52,560 hours (six years of continuous use) using accelerated life testing. The Excel ANOVA table for their experiment is shown below. Some table entries have been obscured. The response variable ( Y) is the number of degraded pixels in a given display. Source of Variation Country of origin

SS 202.9

MS 101.45

Display type

233.2333

58.30833

Interaction

147.7667

18.47084

Error

1096.5

Total

1680.4

F 4.163475

24.36667

Degrees of freedom for display type will be

A) 1. B) 4. C) 3. D) 5.

Version 1

105) A multinational firm manufactures several types of 1280 × 1024 LCD displays in several locations. They designed a sampling experiment to analyze the number of pixels per screen that have significant color degradation after 52,560 hours (six years of continuous use) using accelerated life testing. The Excel ANOVA table for their experiment is shown below. Some table entries have been obscured. The response variable (Y) is the number of degraded pixels in a given display. Source of Variation Country of origin

SS 202.9

MS 101.45

Display type

233.2333

58.30833

Interaction

147.7667

18.47084

Error

1096.5

Total

1680.4

F 4.163475

24.36667

How many display types were there?

A) 1 B) 2 C) 3 D) 5

106) A multinational firm manufactures several types of 1280 × 1024 LCD displays in several locations. They designed a sampling experiment to analyze the number of pixels per screen that have significant color degradation after 52,560 hours (six years of continuous use) using accelerated life testing. The Excel ANOVA table for their experiment is shown below. Some table entries have been obscured. The response variable ( Y) is the number of degraded pixels in a given display. Source of Variation Country of origin Display type

Version 1

SS 202.9 233.2333

MS 101.45

F 4.163475

58.30833

Interaction

147.7667

18.47084

Error

1096.5

Total

1680.4

24.36667

How many countries were studied?

A) 1 B) 2 C) 3 D) 4

107) A multinational firm manufactures several types of 1280 × 1024 LCD displays in several locations. They designed a sampling experiment to analyze the number of pixels per screen that have significant color degradation after 52,560 hours (six years of continuous use) using accelerated life testing. The Excel ANOVA table for their experiment is shown below. Some table entries have been obscured. The response variable ( Y) is the number of degraded pixels in a given display. Source of Variation Country of origin

P-value

202.9

101.45

4.163475

0.021927

Display type

233.2333

58.30833

Interaction

147.7667

18.47084

Error

1096.5

Total

1680.4

F crit

24.36667

TheF statistic for display effect is

Version 1

A) 1.78. B) 3.16. C) 2.39. D) 2.94.

108) A multinational firm manufactures several types of 1280 × 1024 LCD displays in several locations. They designed a sampling experiment to analyze the number of pixels per screen that have significant color degradation after 52,560 hours (six years of continuous use) using accelerated life testing. The Excel ANOVA table for their experiment is shown below. Some table entries have been obscured. The response variable ( Y) is the number of degraded pixels in a given display. Source of Variation Country of origin

P-value

202.9

101.45

4.163475

0.021927

Display type

233.2333

58.30833

Interaction

147.7667

18.47084

Error

1096.5

Total

1680.4

F crit

24.36667

Atα = .05, the interaction effect is

A) clearly significant. B) just barely significant. C) not quite significant. D) clearly insignificant.

Version 1

109) A multinational firm manufactures several types of 1280 × 1024 LCD displays in several locations. They designed a sampling experiment to analyze the number of pixels per screen that have significant color degradation after 52,560 hours (six years of continuous use) using accelerated life testing. The Excel ANOVA table for their experiment is shown below. Some table entries have been obscured. The response variable ( Y) is the number of degraded pixels in a given display. Source of Variation Country of origin

SS 202.9

MS 101.45

Display type

233.2333

58.30833

Interaction

147.7667

18.47084

Error

1096.5

Total

1680.4

F 4.163475

24.36667

The numerator degrees of freedom for the interaction test would be

A) 2. B) 4. C) 8. D) 16.

110) A veterinarian notes the age (months) at which dogs are brought to the clinic to be neutered. Male

Female

Version 1

Collies

Terries

Chows

10 9

14 10

8 18

15 7

17 11

9 15

What kind of test would be used?

A) one-factor ANOVA B) two-factor ANOVA with replication C) two-factor ANOVA without replication D) three-factor ANOVA with replication.

111) A veterinarian notes the age (months) at which dogs are brought in to the clinic to be neutered. Male

Female

Collies

Terries

Chows

10 9

14 10

8 18

15 7

17 11

9 15

Numerator degrees of freedom for the ANOVA interaction test would be

A) 2. B) 3. C) 6. D) impossible to determine.

112) A veterinarian notes the age (months) at which dogs are brought in to the clinic to be neutered. Male

Version 1

Collies

Terries

Chows

Female

15 7

17 11

9 15

Total degrees of freedom for a two-factor replicated ANOVA would be

A) 6. B) 14. C) 17. D) 11.

113)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

How many nozzle settings were observed?

A) 3 B) 2 C) 1 D) cannot tell

114)

Refer to the following partial ANOVA results from Excel (some information is missing).

Version 1

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

Degrees of freedom for pressure level would be

A) 2. B) 3. C) 4. D) 6.

115)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

Error degrees of freedom would be

A) 24. B) 15. C) 12. D) 13.

Version 1

116)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

The overall sample size was

A) 24. B) 23. C) 22. D) 18.

117)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

How many pressure levels were observed?

A) 4 B) 3 C) 2 D) 1

Version 1

118)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting

3.46722

4.87198

0.04751

Pressure level

8.07444

4.03722

5.67291

0.01844

Interaction

2.80779

1.40389

1.97268

0.18177

Error

8.54000

Total

22.8894

P-value F crit

0.711667

At α = .05, the critical F value for nozzle setting is

A) 4.71. B) 4.75. C) 3.68. D) 3.02.

119)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

The form of the original data matrix is

Version 1

A) 3 × 1 table. B) 1 × 2 table. C) 4 × 3 table. D) 2 × 3 table.

120)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

Total

22.8894

The number of replications per treatment was

A) 4. B) 3. C) 2. D) 1.

121)

Refer to the following partial ANOVA results from Excel (some information is missing).

Source of Variation Nozzle setting Pressure level

SS 3.46722 8.07444

df 1

MS 3.46722 4.03722

F 4.87198 5.67291

P-value 0.04751 0.01844

Interaction Error

2.80779 8.54000

1.40389 0.711667

1.97268

0.18177

Total

22.8894

Atα = .05, the effect of nozzle setting is Version 1

A) highly significant. B) just barely significant. C) not quite significant. D) clearly insignificant.

122) As shown below, a hospital recorded the number of minutes spent in post-op recovery by three randomly chosen knee-surgery patients in each category, based on age and type of anesthetic. Which is the most appropriate test?

Anesthetic Type Local

Patient Age Group Under 30 45 60

30 to 49 60 45

75 60

75 120

105 120

120

Spinal

50 and Over 45 75

A) one-factor ANOVA B) two-factor ANOVA without replication C) two-factor ANOVA with replication D) Rimsky-Korsakov test

123) Refer to the following partial ANOVA results from Excel (some information is missing). The response variable was Y = maximum amount of water pumped from wells (gallons per minute). Source of Variation Depth of well Age of well

Version 1

SS 2450 364.667

df 2

MS 1225

3.8371

Interaction

32.667

Error

855.333

Total

3702.667

0.1719 47.519

The degrees of freedom for age of well is

A) 2. B) 3. C) 4. D) 5.

124) Refer to the following partial ANOVA results from Excel (some information is missing). The response variable was Y = maximum amount of water pumped from wells (gallons per minute). Source of Variation Depth of well

SS 2450

df 2

Age of well

364.667

Interaction

32.667

Error

855.333

Total

3702.667

MS 1225

3.8371 0.1719 47.519

TheF statistic for depth of well is

A) 25.23. B) 25.78. C) 25.31. D) 25.06.

Version 1

125) Refer to the following partial ANOVA results from Excel (some information is missing). The response variable was Y = maximum amount of water pumped from wells (gallons per minute). Source of Variation Depth of well

SS 2450

df 2

Age of well

364.667

Interaction

32.667

Error

855.333

Total

3702.667

MS 1225

3.8371 0.1719 47.519

TheMS for interaction is

A) 7.25. B) 8.17. C) 8.37. D) 9.28.

126) Refer to the following partial ANOVA results from Excel (some information is missing). The response variable was Y = maximum amount of water pumped from wells (gallons per minute). Source of Variation Depth of well

SS 2450

df 2

Age of well

364.667

Interaction

32.667

Error

855.333

Total

3702.667

MS 1225

3.8371 0.1719 47.519

TheMS for age of well is

Version 1

A) 185.23. B) 179.26. C) 180.25. D) 182.33.

127)

ANOVA is a procedure intended to compare the variances of several groups (treatments). ⊚ ⊚

128)

true false

ANOVA is a procedure intended to compare the means of several groups (treatments). ⊚ ⊚

true false

129) If you have four factors (call them A, B, C, and D) in an ANOVA experiment with replication, you could have a maximum of four different two-factor interactions. ⊚ ⊚

true false

130) If you have four factors (call them A, B, C, and D) in an ANOVA experiment with replication, you could have a maximum of six different two-factor interactions. ⊚ ⊚

131)

true false

Hartley’s test measures the equality of the means for several groups.

Version 1

⊚ ⊚

132)

true false

Hartley’s test is used to check for unequal variances forc groups. ⊚ ⊚

true false

133) Comparison of c means in one-factor ANOVA can equivalently be done by using c individual t-tests on c pairs of means at the same α. ⊚ ⊚

true false

134) Comparison ofc means in one-factor ANOVA cannot equivalently be done by using c individualt-tests onc pairs of means keeping the chance of Type I error the same. ⊚ ⊚

135)

true false

ANOVA assumes equal variances within each treatment group. ⊚ ⊚

true false

136) Three-factor ANOVA is required if we have three treatment groups (i.e., three data columns). ⊚ ⊚

Version 1

true false

137)

ANOVA assumes normal populations. ⊚ ⊚

138)

ANOVA does not assume normally distributed populations. ⊚ ⊚

139)

true false

Tukey’s test compares pairs of treatment means in an ANOVA. ⊚ ⊚

140)

true false

Tukey's test compares pairs of treatment variances in an ANOVA. ⊚ ⊚

true false

141) Tukey’s test is similar to a two-samplet-test assuming equal varainces except that it pools the variances for allc samples. ⊚ ⊚

142)

true false

Tukey’s test is not needed if we have the overall F statistic for the ANOVA.

Version 1

⊚ ⊚

143)

Interaction plots that show crossing lines indicate likely interactions. ⊚ ⊚

144)

true false

Interaction plots that show parallel lines would suggest interaction effects. ⊚ ⊚

145)

true false

Interaction plots that show parallel lines would suggest no interaction effects. ⊚ ⊚

true false

146) In a two-factor ANOVA with three columns and four rows, there can be more than two interaction effects. ⊚ ⊚

147)

true false

Sample sizes must be equal in one-factor ANOVA. ⊚ ⊚

Version 1

true false

148) In a 3 × 4 randomized block (two-factor unreplicated) ANOVA, we have 12 treatment groups. ⊚ ⊚

true false

149) One-factor ANOVA with two groups is equivalent to a two-samplet-test assuming equal variances. ⊚ ⊚

true false

150) One-factor ANOVA stacked data for five groups will be arranged in five separate columns. ⊚ ⊚

151)

Hartley’s test is the largest sample mean divided by the smallest sample mean. ⊚ ⊚

152)

true false

Tukey’s test for five groups would require 10 comparisons of means. ⊚ ⊚

true false

153) ANOVA is robust to violations of the equal-variance assumption as long as group sizes are equal.

Version 1

⊚ ⊚

true false

154) Levene’s test for homogeneity of variance is attractive because it does not depend on the assumption of normality. ⊚ ⊚

155)

Tukey’s test with seven groups would entail 21 comparisons of means. ⊚ ⊚

156)

true false

Tukey’s test pools all the sample variances. ⊚ ⊚

157)

true false

It is desirable, but not necessary, that sample sizes be equal in a one-factor ANOVA. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 11_7e_Doane 1) B 2) A 3) A 4) B 5) D 6) C 7) B 8) C 9) B 10) D 11) B 12) C 13) B 14) D 15) D 16) D 17) B 18) A 19) B 20) A 21) A 22) A 23) A 24) B 25) C 26) C Version 1

27) A 28) A 29) B 30) A 31) C 32) D 33) C 34) C 35) C 36) B 37) D 38) B 39) D 40) A 41) A 42) C 43) D 44) B 45) A 46) D 47) B 48) C 49) A 50) A 51) B 52) A 53) B 54) B 55) C 56) C Version 1

57) A 58) A 59) D 60) B 61) B 62) C 63) B 64) B 65) D 66) B 67) B 68) A 69) D 70) A 71) C 72) D 73) C 74) D 75) A 76) B 77) A 78) B 79) C 80) A 81) C 82) B 83) D 84) D 85) C 86) A Version 1

87) C 88) B 89) B 90) C 91) C 92) D 93) D 94) B 95) C 96) B 97) C 98) A 99) A 100) B 101) C 102) C 103) B 104) B 105) D 106) C 107) C 108) D 109) C 110) B 111) A 112) C 113) B 114) A 115) C 116) D Version 1

117) B 118) B 119) D 120) B 121) B 122) C 123) A 124) B 125) B 126) D 127) FALSE 128) TRUE 129) FALSE 130) TRUE 131) FALSE 132) TRUE 133) FALSE 134) TRUE 135) TRUE 136) FALSE 137) TRUE 138) FALSE 139) TRUE 140) FALSE 141) TRUE 142) FALSE 143) TRUE 144) FALSE 145) TRUE 146) FALSE Version 1

147) FALSE 148) TRUE 149) TRUE 150) FALSE 151) FALSE 152) TRUE 153) TRUE 154) TRUE 155) TRUE 156) TRUE 157) TRUE

Version 1

CHAPTER 12 1)

The variable used to predict another variable is called the

A) response variable. B) regression variable. C) independent variable. D) dependent variable.

The standard error of the regression

A) is based on squared deviations from the regression line. B) may assume negative values if b1 < 0. C) is in squared units of the dependent variable. D) may be cut in half to get an approximate 95 percent prediction interval.

3) A local trucking company fitted a regression to relate the travel time (days) of its shipments as a function of the distance traveled (miles). The fitted regression is Time = −7.126 + 0.0214 Distance, based on a sample of 20 shipments. The estimated standard error of the slope is 0.0053. Find the value of tcalc to test for zero slope.

A) 2.46 B) 5.02 C) 4.04 D) 3.15

4) A local trucking company fitted a regression to relate the travel time (days) of its shipments as a function of the distance traveled (miles). The fitted regression is Time = −7.126 + .0214 Distance, based on a sample of 20 shipments. The estimated standard error of the slope is 0.0053. Find the critical value for a right-tailed test to see if the slope is positive, using α = .05.

Version 1

A) 2.101 B) 2.552 C) 1.960 D) 1.734

5) If the attendance at a baseball game is to be predicted by the equation Attendance = 16,500 − 75 Temperature, what would be the predicted attendance if Temperature is 90 degrees?

A) 6,750 B) 9,750 C) 12,250 D) 10,020

6) A hypothesis test is conducted at the 5 percent level of significance to test whether the population correlation is zero. If the sample consists of 25 observations and the correlation coefficient is .60, what is the computed test statistic?

A) 2.071 B) 1.960 C) 3.597 D) 1.645

7) Y

TheR2 value is the ratio of the

variation in Y to the

variation in

A) explained; unexplained. B) unexplained; explained. C) explained; total. D) unexplained; total.

Version 1

Which of the following is not a characteristic of the F test in a simple regression?

A) It is a test for overall fit of the model. B) The test statistic can never be negative. C) It requires a table with numerator and denominator degrees of freedom. D) The F test gives a different p-value than the t-test.

9) A researcher’s Excel results are shown below using Femlab (labor force participation rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 U.S. states. Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Variable Coefficients Intercept 343.619889 Femlab −2.2833659

Standard Error 61.0823514 0.99855319

0.313422848 0.098233882 0.079447088 32.07003698 50 t Stat 5.62552 −2.28667

Which of the following statements is not true? A) The standard error is too high for this model to be of any predictive use. B) The 95 percent confidence interval for the coefficient of Femlab is −4.29 to −0.28. C) Significant correlation exists between Femlab and Cancer at α = .05. D) The two-tailed p-value for Femlab will be less than .05.

10) A researcher’s results are shown below using Femlab (labor force participation rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 U.S. states.

Version 1

Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Variable Coefficients Intercept 343.619889 Femlab −2.2833659

Standard Error 61.0823514 0.99855319

0.313422848 0.098233882 0.079447088 32.07003698 50 t Stat 5.62552 −2.28667

Which statement is valid regarding the relationship between Femlab and Cancer? A) A rise in female labor participation rate will cause the cancer rate to decrease within a state. B) This model explains about 10 percent of the variation in state cancer rates. C) At the .05 level of significance, there isn’t enough evidence to say the two variables are related. D) If your sister starts working, the cancer rate in your state will decline.

11) A researcher’s results are shown below using Femlab (labor force participation rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 U.S. states. Source of variation Regression Residual

df 1 48

SS 5377.836 49367.389

Total

54745.225

MS 5377.836 1028.487

F 5.228879

What is the R2 for this regression? A) .9018 B) .0982 C) .8395 D) .1605

Version 1

12) A news network stated that a study had found a positive correlation between the number of children a worker has and his or her earnings last year. You may conclude that

A) people should have more children so they can get better jobs. B) the data are erroneous because the correlation should be negative. C) correlation does not demonstrate causation. D) statisticians have small families.

13) William used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). His estimated regression equation was Crime = 428 + 0.050 Income. We can conclude that

A) there is no significant relationship between income and crime. B) crime causes additional income in each city. C) wealthy individuals tend to commit most crimes. D) the intercept is irrelevant because zero median income makes no sense.

14) Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 1000, we would expect that Crime will

A) increase by 428. B) decrease by 50. C) increase by 500. D) remain unchanged.

15)

If the best estimate forY is the mean ofY then the correlation betweenX andY is

Version 1

A) positive. B) zero. C) negative. D) unknown.

16) Amelia used a random sample of 100 accounts receivable to estimate the relationship between Days (number of days from billing to receipt of payment) and Size (size of balance due in dollars). Her estimated regression equation was Days = 22 + 0.0047 Size with a correlation coefficient of .300. From this information we can conclude that

A) 9 percent of the variation in Days is explained by Size. B) autocorrelation is likely to be a problem. C) the relationship between Days and Size is significant. D) larger accounts usually take less time to pay.

17)

Prediction intervals for Y are narrowest when

A) the mean of X is near the mean of Y. B) the value of X is near the mean of X. C) the mean of X differs greatly from the mean of Y. D) the mean of X is small.

18)

If n = 15 and r = .4296, the corresponding t statistic to test for zero correlation is

A) 1.715. B) 7.862. C) 2.048. D) impossible to determine without α.

Version 1

19) Using a two-tailed test at α = .05 for n = 30, we would reject the hypothesis of zero correlation if the absolute value of r exceeds

A) .2992. B) .3609. C) .0250. D) .2004.

20)

The ordinary least squares (OLS) method of estimation will minimize

A) neither the slope nor the intercept. B) only the slope. C) only the intercept. D) both the slope and intercept.

21)

A standardized residual equal to −2.205 indicates

A) a rather poor prediction. B) an extreme outlier in the residuals. C) an observation with high leverage. D) a likely data entry error.

22)

In a simple regression, which would suggest a significant relationship between X and Y?

Version 1

A) large p-value for the estimated slope B) large t statistic for the slope C) large p-value for the F statistic D) small t statistic for the slope

23) If there is no significant correlation between the response and explanatory variables then the slope of the regression line would be

A) positive. B) negative. C) zero. D) unknown.

24)

Which is indicative of an inverse relationship between X and Y?

A) a negative F statistic B) a negative p-value for the correlation coefficient C) a negative correlation coefficient D) either a negative F statistic or a negative p-value

25)

Which is not correct regarding the estimated slope of the OLS regression line?

A) It is divided by its standard error to obtain its t statistic. B) It shows the change in Y for a unit change in X. C) It is chosen so as to minimize the sum of squared errors. D) It may be regarded as zero if its p-value is less than α.

Version 1

26)

Simple regression analysis means that

A) the data are presented in a simple and clear way. B) we have only a few observations. C) there are only two independent variables. D) we have only one explanatory variable.

27)

The sample coefficient of correlation does not have which property?

A) It can range from −1.00 up to +1.00. B) It is also sometimes called Pearson’s r. C) It is tested for significance using a t-test. D) It assumes that Y is the dependent variable.

28) When comparing the 90 percent prediction and confidence intervals for a given regression analysis

A) the prediction interval is narrower than the confidence interval. B) the prediction interval is wider than the confidence interval. C) there is no difference between the size of the prediction and confidence intervals. D) no generalization is possible about their comparative width.

29)

Which is not true of the coefficient of determination?

A) It is the square of the coefficient of correlation. B) It is negative when there is an inverse relationship between X and Y. C) It reports the percentage of the variation in Y explained by X. D) It is calculated using sums of squares (e.g., SSR, SSE, SST).

Version 1

30) that

If the fitted regression is Y = 3.5 + 2.1 X ( R2 = .25, n = 25), it is incorrect to conclude

A) Y increases 2.1 percent for a 1 percent increase in X. B) the estimated regression line crosses the Y axis at 3.5. C) the sample correlation coefficient must be positive. D) the value of the sample correlation coefficient is .50.

In a simple regression Y = b0 + b1 X where Y = number of robberies in a city (thousands 31) of robberies), X = size of the police force in a city (thousands of police), and n = 45 randomly chosen large U.S. cities in 2008, we would be least likely to see which problem?

A) autocorrelated residuals (because this is time-series data) B) heteroscedastic residuals (because we are using totals uncorrected for city size) C) nonnormal residuals (because a few larger cities may skew the residuals) D) high leverage for some observations (because some cities may be huge)

32) When homoscedasticity exists, we would expect that a plot of the residuals versus the fitted Y

A) will form approximately a straight line. B) crosses the centerline too many times. C) will yield a Durbin-Watson statistic near 2. D) will show no pattern at all.

33)

Which statement is not correct?

Version 1

A) Spurious correlation can often be reduced by expressing X and Y in per capita terms. B) Autocorrelation is mainly a concern when we are using time-series data. C) Heteroscedastic residuals will have roughly the same variance for any value of X. D) Standardized residuals make it easy to identify outliers or instances of poor fit.

34) In a simple bivariate regression with 25 observations, which statement is most nearly correct?

A) A nonstandardized residual whose value is ei = 4.22 would be considered an outlier. B) A leverage statistic of 0.16 or more would indicate high leverage. C) Standardizing the residuals will eliminate any heteroscedasticity. D) Nonnormal residuals imply biased coefficient estimates, a major problem.

35) A regression was estimated using these variables: Y = annual value of reported bank robbery losses in all U.S. banks ($ millions), X = annual value of currency held by all U.S. banks ($ millions), n = 100 years (1912 through 2011). We would not anticipate

A) autocorrelated residuals due to time-series data. B) heteroscedastic residuals due to the wide variation in data magnitudes. C) nonnormal residuals due to skewed data as bank size increases over time. D) a negative slope because banks hold less currency when they are robbed.

36) A fitted regression for an exam in Prof. Hardtack’s class showed Score = 20 + 7 Study, where Score is the student’s exam score and Study is the student’s study hours. The regression yielded R2 = 0.50 and SE = 8. Bob studied 9 hours. The quick 95 percent prediction interval for Bob’s grade is approximately

Version 1

A) 69 to 97. B) 75 to 91. C) 67 to 99. D) 76 to 90.

37)

Which is not an assumption of least squares regression?

A) normal X values B) nonautocorrelated errors C) homoscedastic errors D) normal errors

38) The following scatter plot shows the state foreclosure rate and the state’s share of all new mortgages that were subprime for a given year. Based on the plot, which residual assumption violation will you expect to see in the regression analysis?

Version 1

A) normal X values B) nonautocorrelated errors C) homoscedastic errors D) normal errors

39)

In a simple bivariate regression with 60 observations, there will be

residuals.

A) 60 B) 59 C) 58 D) 57

40)

Which is correct to find the value of the coefficient of determination ( R2)?

A) SSR/ SSE B) SSR/ SST C) 1 − SST/ SSE D) SST/SSR

The critical value for a two-tailed test of H0: β1 = 0 at α = .05 in a simple regression with 41) 22 observations is

A) ±1.725. B) ±2.086. C) ±2.528. D) ±1.960.

Version 1

42) In a sample of size n = 23, a sample correlation of r = .400 provides sufficient evidence to conclude that the population correlation coefficient exceeds zero in a right-tailed test at

A) α = .01 but not α = .05. B) α = .05 but not α = .01. C) both α = .05 and α = .01. D) neither α = .05 nor α = .01.

43)

In a sample of n = 23, the Student’s t test statistic for a correlation of r = .500 would be

A) 2.559. B) 2.819. C) 2.646. D) impossible to calculate without knowing α.

44) In a sample of n = 23, the critical value of the correlation coefficient for a two-tailed test at α = .05 is

A) ±.524. B) ±.412. C) ±.500. D) ±.497.

45) In a sample of n = 23, the critical value of Student’s t for a two-tailed test of significance for a simple bivariate regression at α = .05 is

Version 1

A) ±2.229. B) ±2.819. C) ±2.646. D) ±2.080.

46) In a sample of n = 40, a sample correlation of r = .400 provides sufficient evidence to conclude that the population correlation coefficient exceeds zero in a right-tailed test at

A) α = .025 but not α = .05. B) α = .05 but not α = .025. C) both α = .025 and α = .05. D) neither α = .025 nor α = .05.

47)

In a sample of n = 20, the Student’s t test statistic for a correlation of r = .400 would be

A) 2.110. B) 1.645. C) 1.852. D) can’t say without knowing if it’s a two-tailed or one-tailed test .

48) In a sample of n = 20, the critical value of the correlation coefficient for a two-tailed test at α = .05 is

A) ±.587. B) ±.412. C) ±.444. D) ±.497.

Version 1

49) In a sample of n = 27, the critical value of Student’s t for a two-tailed test of significance for a simple bivariate regression at α = .05 is

A) ±2.060. B) ±2.052. C) ±2.898. D) ±2.074.

50) In a sample of size n = 36, a sample correlation of r = −.450 provides sufficient evidence to conclude that the population correlation coefficient differs significantly from zero in a twotailed test at

A) α = .01. B) α = .05. C) both α = .01 and α = .05. D) neither α = .01 nor α = .05.

51)

In a sample of n = 36, the Student’s t test statistic for a correlation of r = −.450 would be

A) −2.110. B) −2.938. C) −2.030. D) impossible to calculate without knowing α.

52) In a sample of n = 36, the critical value of the correlation coefficient for a two-tailed test at α = .05 is

Version 1

A) ±.329. B) ±.387. C) ±.423. D) ±.497.

53) In a sample of n = 36, the critical value of Student’s t for a two-tailed test of significance of the slope for a simple regression at α = .05 is

A) 2.938. B) 2.724. C) 2.032. D) 2.074.

54) A local trucking company fitted a regression to relate the travel time (days) of its shipments as a function of the distance traveled (miles). The fitted regression is Time = −7.126 + 0.0214 Distance. If Distance increases by 50 miles, the expected Time would increase by

A) 1.07 days. B) 7.13 days. C) 2.14 days. D) 1.73 days.

Version 1

55) A local trucking company fitted a regression to relate the cost of its shipments as a function of the distance traveled. The Excel fitted regression is shown.

Based on this estimated relationship, when distance increases by 50 miles, the expected shipping cost would increase by how much? A) $286 B) $143 C) $104 D) $301

56)

If SSR is 2592 and SSE is 608, then

A) the slope is likely to be insignificant. B) the coefficient of determination is .81. C) the SST would be smaller than SSR. D) the standard error would be large.

57)

Find the sample correlation coefficient for the following data. X

Y 3 7

Version 1

8 12

5 9 11 13 15 17

13 10 17 23 35 34

A) .8911 B) .9124 C) .9822 D) .9556

58)

Find the slope of the simple regression of Y on X. X

Y 3 7 5 9 11 13 19 21

8 12 13 10 17 23 39 38

A) 1.833 B) 3.294 C) 0.762 D) −2.228

59)

Find the sample correlation coefficient for the following data. X

Y 3 5 9

Version 1

9 13 10

13 15

23 35

A) .7291 B) .8736 C) .9118 D) .9563

60)

Find the slope of the simple regression of Y on X. X

Y 3 5 9 13 15

9 13 10 23 35

A) 2.595 B) 1.109 C) −2.221 D) 1.884

61)

A researcher’s results are shown below using n = 25 observations.

Variable Intercept Slope

Coefficients 343.619889 −2.2833659

Standard Error 61.0823514 0.99855319

Which is the 95 percent confidence interval for the slope? A) [−3.282, −1.284] B) [−4.349, −0.217] C) [1.118, 5.026] D) [−0.998, +0.998]

Version 1

62)

A researcher’s regression results are shown below using n = 8 observations.

Variable Intercept Slope

Coefficients −0.1667 1.8333

Standard Error 2.8912 0.2037

Which is the 95 percent confidence interval for the slope? A) [1.333, 2.284] B) [1.602, 2.064] C) [1.268, 2.398] D) [1.118, 2.449]

63)

Bob thinks there is something wrong with Excel’s fitted regression. What do you say?

A) The estimated equation is obviously incorrect. B) The R2 looks a little high but otherwise it looks okay. C) Bob needs to increase his sample size to decide. D) The relationship is linear, so the equation is credible.

64)

The error term εi in the population regression model yi = β0 + β1 xi + εi is assumed to be

Version 1

A) observable. B) autocorrelated. C) heteroscedastic. D) normally distributed.

65)

Which is not an assumed property of the errors in a population regression model?

A) They are unobservable. B) They are independent. C) They have zero variance. D) They are normally distributed.

66) If the residuals from a fitted regression violate the assumption of homoscedasticity, we know that

A) they are normally distributed. B) they are independent of one another. C) their variance is not constant. D) there are extreme outliers.

67)

If the residuals violate the assumption of autocorrelation, we know that they

A) are probably outliers. B) are not independent. C) have constant variance. D) are normally distributed.

Version 1

68)

If the residuals violate the assumption of normality, we expect that

A) the sample was not taken randomly. B) the residuals will not sum to zero. C) least squares formulas will fail. D) confidence intervals may be unreliable.

69)

Which is not an assumed characteristic of εi in the population model yi = β0 + β1 xi + εi?

A) It is a random variable. B) It has zero mean. C) It is a statistic. D) It is unobservable.

70)

To calculate a residual for the ith observation, we do not need the

A) actual value of yi. B) estimated slope. C) standard error. D) estimated intercept.

71)

In the population model yi = β0 + β1 xi + εi the βj are

A) parameters. B) statistics. C) estimated. D) observable.

Version 1

72)

The slope of a proposed population regression model yi = β0 + β1 xi + εi is assumed to be

A) a random variable. B) distributed normally. C) a statistic. D) a parameter.

73) A fitted regression Profit = 262 + 1.51 Sales (all variables in thousands of dollars) was estimated from a random sample of 15 small coffee kiosks . We can say that

A) the slope is too small to be significant. B) the intercept does not seem reasonable. C) the R2 will be low due to small sample size. D) predictions are likely to be underestimated.

74) A fitted regression Profit = −570 + 30 Sales (all variables in thousands of dollars) was estimated from a random sample of 20 pharmacies . For a pharmacy with Sales = 10, we predict that Profit will be

A) 3570. B) 2430. C) −270. D) 870.

75) A fitted regression Profit = −570 + 30 Sales (all variables in thousands of dollars) was estimated from a random sample of pharmacies . From this regression, in order to break even ( Profit ≥ 0), a pharmacy’s Sales would have to be at least

Version 1

A) 19. B) 300. C) 56. D) 100.

76) A financial regression yielded a standard error of 12 dollars, so a residual of 23 dollars would be

A) a rather poor prediction. B) an extreme outlier in the residuals. C) an observation with high leverage. D) an outlier, but not extreme.

77)

A variable transformation in a regression (e.g., replacing Y with log( Y))

A) may reduce heteroscedasticity. B) changes the model specification. C) makes the model easier to interpret. D) leads to severe autocorrelation.

78)

The estimated intercept in a regression

A) is often of secondary interest to the researcher. B) should be forced to zero in the estimated model. C) can be omitted when making predictions. D) is greater than zero as long as Y is positive.

Version 1

79)

We would use a logistic regression model

A) to estimate a log-linear trend in time-series data. B) when the residuals are not normally distributed. C) to predict an event that occurs or does not occur. D) with Excel’s exponential trend regression model.

80)

Which is not a characteristic of the logistic regression model?

A) It postulates an S-shaped relationship between X and Y. B) It can best be fitted using the maximum likelihood method. C) Predictions from the fitted logit model are either 0 or 1. D) The logistic model cannot yield predictions greater than 1.

If you were to use Excel to estimate Y = β0 + β1 X + ε with binary Y (0 or 1) you would 81) expect

A) an error message because Excel does not allow a binary Y. B) predicted probabilities greater than 1 or less than 0. C) predictions that are either 0 or 1. D) residuals that are homoscedastic and normally distributed.

82) Professor Axolotl kept track of labs attended and midterm exam scores for the students in his statistics class. To see whether there was a relationship, she fitted a regression. The result was Score= 67.654 +3.2752 Labs with standard errorse = 5.6301. One student scored 95 on the midterm but only attended 6 labs. Which of the following is true about this score?

Version 1

A) This score results in a negative residual and is an outlier. B) This score results in a negative residual and is not an outlier. C) This score results in a positive residual and is not an outlier. D) This score results in a positive residual and is an outlier.

83) A local trucking company fitted a regression to relate the cost of its shipments as a function of the distance traveled. The Excel fitted regression is shown.

How many degrees of freedom would we use to perform a t-test for zero slope H0: β1 = 0? A) 22 B) 20 C) 18 D) 21

Version 1

84) A local trucking company fitted a regression to relate the cost of its shipments as a function of the distance traveled. The Excel fitted regression is shown.

The value of the correlation coefficient is approximately A) .921. B) .848. C) .719. D) .559.

85) A scatter plot is used to visualize the association (or lack of association) between two quantitative variables. ⊚ ⊚

true false

86) The correlation coefficient r measures the strength of the linear relationship between two variables. ⊚ ⊚

Version 1

true false

87)

Pearson’s correlation coefficient ( r) requires that both variables be interval or ratio data. ⊚ ⊚

88)

If r = .55 and n = 16, then the correlation is significant atα = .05 in a two-tailed test. ⊚ ⊚

89)

true false

A sample correlationr = .40 indicates a stronger linear relationship thanr = −.60. ⊚ ⊚

90)

true false

A sample correlationr = −.60 indicates a stronger linear relationship thanr = .40. ⊚ ⊚

true false

91) A common source of spurious correlation between X and Y is when a third unspecified variable Z affects both X and Y. ⊚ ⊚

92)

true false

The correlation coefficient r always has the same sign as b1 in Y = b0 + b1 X.

Version 1

⊚ ⊚

93)

true false

The fitted intercept in a regression has little meaning ifX = 0 is not a plausible outcome. ⊚ ⊚

true false

94) The least squares regression line is obtained when the sum of the squared residuals is minimized. ⊚ ⊚

true false

95) In a simple regression, if the coefficient for X is positive and significantly different from zero, then an increase in X is associated with an increase in the mean (i.e., the expected value) of Y. ⊚ ⊚

96)

In least squares regression, the residuals e1, e2, . . . , en will always have a zero mean. ⊚ ⊚

97)

true false

When using the least squares method, the column of residuals always sums to zero. ⊚ ⊚

Version 1

true false

98) In the model Sales = 268 + 7.37 Ads (both variables in dollars) an additional $1 spent on ads will increase sales by 7.37 percent. ⊚ ⊚

true false

99) IfR2 = .49 in a bivariate regression then the correlation coefficient forX andY is either −.7 or +.7. ⊚ ⊚

true false

100) If R2 = .36 in the model Sales = 268 + 7.37 Ads with n = 50, the two-tailed test for correlation at α = .05 would say that there is a significant correlation between Sales and Ads. ⊚ ⊚

true false

101) If R2 = .36 in the model Sales = 268 + 7.37 Ads, then Ads explains 36 percent of the variation in Sales. ⊚ ⊚

102)

true false

The ordinary least squares regression line always passes through the point ⊚ ⊚

Version 1

true false

103)

The least squares regression line gives unbiased estimates of β0 and β1. ⊚ ⊚

104)

In a simple regression, the correlation coefficient r is the square root of R2. ⊚ ⊚

105)

true false

IfSSR is 1800 andSSE is 200, thenR2 is .10. ⊚ ⊚

107)

true false

If SSR is 1800 and SSE is 200, then R2 is .90. ⊚ ⊚

106)

true false

The standard error for an individual value is less than the standard error se. ⊚ ⊚

true false

108) If SSE is near zero in a regression, the statistician will conclude that the proposed model probably has too poor a fit to be useful. ⊚ ⊚

Version 1

true false

109) For a regression with 200 observations, we expect that about 10 residuals will exceed two standard errors. ⊚ ⊚

110)

true false

Confidence intervals for predicted Y are less precise when the residuals are very small. ⊚ ⊚

true false

111) Cause-and-effect direction between X and Y may be determined by running the regression twice and seeing whether Y = β0 + β1 X or X = β1 + β0 Y has the larger R2. ⊚ ⊚

true false

112) The ordinary least squares method of estimation minimizes the estimated slope and intercept. ⊚ ⊚

113)

The ordinary least squares method ensures that the residuals will be normally distributed. ⊚ ⊚

114)

true false

If you have a strong outlier in the residuals, it may represent a different causal system.

Version 1

⊚ ⊚

true false

115) A negative correlation between two variables X and Y usually yields a negative p-value for r. ⊚ ⊚

true false

116) In linear regression between two variables, a significant relationship exists when the pvalue of the t test statistic for the slope is greater than α. ⊚ ⊚

true false

117) The larger the absolute value of the t statistic of the slope in a simple linear regression, the stronger the linear relationship that exists between X and Y. ⊚ ⊚

true false

118) In simple linear regression, the coefficient of determination ( R2) is estimated from sums of squares in the ANOVA table. ⊚ ⊚

true false

119) In simple linear regression, the p-value of the slope will always equal the p-value of the F statistic. ⊚ ⊚

Version 1

true false

120)

An observation with high leverage will have a large residual (usually an outlier). ⊚ ⊚

true false

121) A prediction interval for Y is narrower than the corresponding confidence interval for the mean of Y. ⊚ ⊚

true false

122) When X is farther from its mean, the prediction interval and confidence interval for Y become wider. ⊚ ⊚

123)

true false

The total sum of squares ( SST) will never exceed the regression sum of squares ( SSR). ⊚ ⊚

true false

124) The regression sum of squares (SSR) will will always be greater than the error sum of squares (SSE). ⊚ ⊚

Version 1

true false

125) "High leverage" would refer to a data point that is poorly predicted by the model (large residual). ⊚ ⊚

true false

126) Studentized (or standardized) residuals permit us to detect cases where the regression predicts poorly. ⊚ ⊚

127)

true false

A poor prediction (large residual) indicates an observation with high leverage. ⊚ ⊚

true false

128) Ill-conditioned refers to a variable whose units are too large or too small (e.g., $2,434,567). ⊚ ⊚

true false

129) A simple decimal transformation (e.g., from 18,291 to 18.291) often improves data conditioning. ⊚ ⊚

true false

130) Two-tailed t-tests are often used because any predictor that differs significantly from zero in a two-tailed test will also be significantly greater than zero or less than zero in a one-tailed test at the same α.

Version 1

⊚ ⊚

true false

131) A predictor that is significant in a one-tailed t-test will also be significant in a two-tailed test at the same level of significance α. ⊚ ⊚

132)

Omission of a relevant predictor is a common source of model misspecification. ⊚ ⊚

133)

true false

Using the least squares formulas, the regression line must pass through the origin. ⊚ ⊚

134)

true false

Outliers can be detected by examining the standardized residuals. ⊚ ⊚

true false

135) In a simple regression, there aren − 2 degrees of freedom associated with the error sum of squares(SSE). ⊚ ⊚

Version 1

true false

136)

In a simple regression, the F statistic is calculated by taking the ratio of MSR to the MSE. ⊚ ⊚

true false

137) The coefficient of determination is the percentage of the total variation in the response variable Y that is explained by the predictor X. ⊚ ⊚

138) X.

A different confidence interval exists for the mean value of Y for each different value of

⊚ ⊚

139)

true false

A prediction interval for Y is widest when X is near its mean. ⊚ ⊚

true false

140) In a two-tailed test for correlation at α = .05, a sample correlation coefficient r = .42 with n = 25 is significantly different than zero. ⊚ ⊚

141)

true false

In correlation analysis, neither X nor Y is designated as the independent variable. ⊚ ⊚

Version 1

true false

142) A negative value for the correlation coefficient ( r) implies a negative value for the slope ( b1). ⊚ ⊚

143)

true false

High leverage for an observation indicates that X is far from its mean. ⊚ ⊚

true false

144) Autocorrelated errors are not usually a concern for regression models using crosssectional data. ⊚ ⊚

true false

145) There are usually several possible regression lines that will minimize the sum of squared errors. ⊚ ⊚

true false

146) When the errors in a regression model are not independent, the regression model is said to have autocorrelation. ⊚ ⊚

Version 1

true false

147)

In a simple bivariate regression, Fcalc = tcalc2. ⊚ ⊚

true false

148) Correlation analysis primarily measures the degree of the linear relationship between X and Y. ⊚ ⊚

true false

149) Linear regression using ordinary least squares requires that the response variable be quantitative. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 12_7e_Doane 1) C 2) A 3) C 4) D 5) B 6) C 7) C 8) D 9) A 10) B 11) B 12) C 13) D 14) B 15) B 16) A 17) B 18) A 19) B 20) A 21) A 22) B 23) C 24) C 25) D 26) D Version 1

27) D 28) B 29) B 30) A 31) A 32) D 33) C 34) B 35) D 36) C 37) A 38) C 39) A 40) B 41) B 42) B 43) C 44) B 45) D 46) C 47) C 48) C 49) A 50) C 51) B 52) A 53) C 54) A 55) B 56) B Version 1

57) B 58) A 59) B 60) D 61) B 62) C 63) A 64) D 65) C 66) C 67) B 68) D 69) C 70) C 71) A 72) D 73) B 74) C 75) A 76) A 77) A 78) A 79) C 80) C 81) B 82) C 83) B 84) A 85) TRUE 86) TRUE Version 1

87) TRUE 88) TRUE 89) FALSE 90) TRUE 91) TRUE 92) TRUE 93) TRUE 94) TRUE 95) TRUE 96) TRUE 97) TRUE 98) FALSE 99) TRUE 100) TRUE 101) TRUE 102) TRUE 103) TRUE 104) TRUE 105) TRUE 106) FALSE 107) FALSE 108) FALSE 109) TRUE 110) FALSE 111) FALSE 112) FALSE 113) FALSE 114) TRUE 115) FALSE 116) FALSE Version 1

117) TRUE 118) TRUE 119) TRUE 120) FALSE 121) FALSE 122) TRUE 123) FALSE 124) FALSE 125) FALSE 126) TRUE 127) FALSE 128) TRUE 129) TRUE 130) TRUE 131) FALSE 132) TRUE 133) FALSE 134) TRUE 135) TRUE 136) TRUE 137) TRUE 138) TRUE 139) FALSE 140) TRUE 141) TRUE 142) TRUE 143) TRUE 144) TRUE 145) FALSE 146) TRUE Version 1

147) TRUE 148) TRUE 149) TRUE

Version 1

CHAPTER 13 1) In a multiple regression with six predictors in a sample of 67 U.S. cities, what would be the critical value for an F test of overall significance at α = .05?

A) 2.29 B) 2.25 C) 2.37 D) 2.18

2) In a multiple regression with five predictors in a sample of 56 U.S. cities, what would be the critical value for an F test of overall significance at α = .05?

A) 2.45 B) 2.37 C) 2.40 D) 2.56

3) When predictor variables are strongly related to each other, the regression estimates is questionable.

of the

A) logic B) fit C) parsimony D) stability

4) When a multiple regression model has two significant predictors and five insignificant predictors which of the following concepts are disregarded?

Version 1

A) logic. B) fit. C) parsimony. D) stability.

5) A test is conducted in 22 cities to see if giving away free transit system maps will increase the number of bus riders. In a regression analysis, the dependent variable Y is the increase in bus riders (in thousands of persons) from the start of the test until its conclusion. The independent variables are X1 = the number (in thousands) of free maps distributed and a binary variable X2 = 1 if the city has free downtown parking, 0 otherwise. The estimated regression equation isY = 1.32 + 0.0345X1 − 1.45X2 . In city 3, the observed Y value is 7.3, X1 = 140, and X2 = 0. The residual for city 3 (in thousands) is

A) 6.15 B) 1.15 C) 4.83 D) 1.57

If X2 is a binary predictor in Y = β0 + β1 X1 + β2 X2, then which statement is most nearly 6) correct?

A) X2 = 1 should represent the most desirable condition. B) X2 would be a significant predictor if β2 = 423.72. C) X2 = 0, X2 = 1, X2 = 2 would be appropriate if three categories exist. D) X2 will shift the estimated equation either by 0 units or by β2 units.

IfX2 is a binary predictor inY =β0 +β1X1 +β2X2, then which statement is most nearly 7) correct?

Version 1

A) X2 = 0 would represent the case when theX2 condition is not present. B) X2 would be a significant predictor only ifβ1 is significant. C) There could be up to four different categories for theX2 predictor. D) X2 will equal 1 unit ifX2 is significant.

The unexplained sum of squares measures variation in the dependent variable Y about the

A) mean of the Y values. B) estimated Y values. C) mean of the X values. D) Y-intercept.

Which of the following is not true of the standard error of the regression?

A) It is a measure of the accuracy of the prediction. B) It is based on squared vertical deviations between the actual and predicted values of Y. C) It would be negative when there is an inverse relationship in the model. D) It is used in constructing confidence and prediction intervals for Y.

10) A multiple regression analysis with two independent variables yielded the following results in the ANOVA table: SS(Total) = 798, SS(Regression) = 738, SS(Error) = 60. The multiple correlation coefficient is

A) .2742. B) .0752. C) .9248. D) .9617.

Version 1

11) A multiple regression analysis with two independent variables yielded the following results in the ANOVA table:SS(Total) = 798,SS(Regression) = 738,SS(Error) = 60. The coefficient of deterimination is

A) .2742. B) .0752. C) .9248. D) .9617.

12) A multiple regression analysis with two independent variables yielded the following results in the ANOVA table:SS(Total) = 798, SS(Regression) = 738,SS(Error) = 60. TheF statistic is

A) .2742. B) not possible to calculate. C) .9248. D) .9617.

A fitted multiple regression equation is Y = 12 + 3 X1 − 5 X2 + 7 X3 + 2 X4. When X1 13) increases 2 units and X2 increases 2 units as well, while X3 and X4 remain unchanged, what change would you expect in your estimate of Y?

A) Decrease by 2. B) Decrease by 4. C) Increase by 2. D) No change inY.

Version 1

A fitted multiple regression equation is Y = 28 + 5 X1 − 4 X2 + 7 X3 + 2 X4. When X1 14) increases 2 units and X2 increases 2 units as well, while X3 and X4 remain unchanged, what change would you expect in your estimate of Y?

A) Increase by 2. B) Decrease by 4. C) Increase by 4. D) No change in Y.

15) Which is not a name often given to an independent variable that takes on just two values (0 or 1) according to whether or not a given characteristic is absent or present?

A) Absent variable B) Binary variable C) Dummy variable D) Indicator variable

16) Using a sample of 63 observations, a dependent variableY is regressed against two variablesX1 andX2 to obtain the fitted regression equationY = 76.40 − 6.388X1 + 0.870X2. The standard error ofb1 is 3.453 and the standard error ofb2 is 0.611.tcalc forβ1 =

A) −6.388. B) −0.5405. C) −1.849. D) −1.424.

17) Using a sample of 63 observations, a dependent variableY is regressed against two variablesX1 andX2 to obtain the fitted regression equationY = 76.40 − 6.388X1 + 0.870X2. The standard error ofb1 is 3.453 and the standard error ofb2 is 0.611.tcalc forβ2 =

Version 1

A) +6.388. B) +0.5405. C) +1.849. D) +1.424.

18) Using a sample of 63 observations, a dependent variable Y is regressed against two variables X1 and X2 to obtain the fitted regression equation Y = 76.40 − 6.388 X1 + 0.870 X2. The standard error of b1 is 3.453 and the standard error of b2 is 0.611. At α = .05, we could

A) conclude that both coefficients differ significantly from zero. B) reject H0: β1 ≥ 0 and conclude H1: β1 < 0 . C) reject H0: β1 ≤ 0 and conclude H1: β1 > 0 . D) conclude that Evans’ Rule has been violated.

19)

Refer to this ANOVA table from a regression:

Source Regression Residual

df 4 45

SS 1793.2356 2695.0996

Total

4488.3352

MS 448.3089 59.8911

F 7.48540

Which statement is not accurate? A) The F test is significant at α = .05. B) There were 50 observations. C) There were 5 predictors. D) There would be 50 residuals.

Version 1

20)

Refer to this ANOVA table from a regression:

Source Regression Residual

df 4 45

SS 1793.2356 2695.0996

Total

4488.3352

MS 448.3089 59.8911

F 7.48540

For this regression, the R2 is A) .3995. B) .6005. C) .6654. D) .8822.

21) Refer to the following regression results. The dependent variable is Abort (the number of abortions per 1000 women of childbearing age). The regression was estimated using data for the 50 U.S. states with these predictors: EdSpend = public K − 12 school expenditure per capita, Age = median age of population, Unmar = percent of total births by unmarried women, Infmor = infant mortality rate in deaths per 1000 live births. Variable

Coefficients

Intercept EdSpend Age Unmar InfMor

−19.244 0.0080040 0.76012 0.98629 −3.7848

Standard Error 25.387 0.0054472 0.66914 0.22132 1.0173

t-Statistic −0.758 1.469 1.136 4.456 −3.720

Which statement is not supported by a two-tailed test? A) Unmar is a significant predictor at α = .01. B) EdSpend is a significant predictor at α = .20. C) Infmor is not a significant predictor at α = .05. D) Age is not a significant predictor at α = .05.

Version 1

22) Refer to the following correlation matrix that was part of a regression analysis. The dependent variable was Abort (the number of abortions per 1000 women of childbearing age). The regression was estimated using data for the 50 U.S. states with these predictors: EdSpend = public K − 12 school expenditure per capita, Age = median age of population, Unmar = percent of total births by unmarried women, Infmor = infant mortality rate in deaths per 1000 live births. Correlation Matrix Abort Abort

EdSpend

Age

Unmar

InfMor

1.0000

EdSpend

0.2626

1.0000

Age

0.1610

−0.0420

1.0000

Unmar

0.3286

−0.0949

0.0937

1.0000

InfMor

−0.2513

−0.2826

0.0389

0.5239

1.0000

Using a two-tailed correlation test, which statement is not accurate? A) Age and Infmor are not significantly correlated at α = .05. B) Abort and Unmar are significantly correlated at α = .05. C) Unmar and Infmor are significantly correlated at α = .05. D) The first column of the table shows evidence of multicollinearity.

23)

Part of a regression output is provided below. Some of the information has been omitted.

Source of variation Regression

SS 3177.17

Residual Total

3478.36

df 2

MS 1588.6

17.717

The approximate value of F is

Version 1

A) 1605.7. B) 0.9134. C) 89.66. D) impossible to calculate with the given information.

24)

Part of a regression output is provided below. Some of the information has been omitted.

Source of variation Regression

SS 3177.17

Residual Total

3478.36

df 2

MS 1588.6

17.717

The SS (residual) is A) 3177.17. B) 301.19. C) 17.71. D) impossible to determine.

25) A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a fireplace ( FP is 0 if there is no fireplace, 1 if there is a fireplace). Part of the regression output is provided below, based on a sample of 20 homes. Some of the information has been omitted. Variable

Coefficients

Intercept Size

128.93746

6.47601954

Standard Error 2.6205302 1.2072436

t-Statistic

1.9803612

3.27

49.203 11.439

The estimated coefficient for Size is approximately

Version 1

A) 9.5. B) 13.8. C) 122.5. D) 1442.6.

26) A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a fireplace ( FP is 0 if there is no fireplace, 1 if there is a fireplace). The regression output is provided below. Some of the information has been omitted. Source of variation Regression

SS 3177.17

Residual Total

3478.36

df 2

MS 1588.6

17.717

How many predictors (independent variables) were used in the regression? A) 20 B) 18 C) 3 D) 2

27) A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a fireplace ( FP is 0 if there is no fireplace, 1 if there is a fireplace). The regression output is provided below. Some of the information has been omitted. Source of variation Regression Residual

Version 1

SS 3177.17

df 2

MS 1588.584

17.71713

Total

3478.36

Which of the following conclusions can be made based on the F test? A) Thep-value on theF test will be very high. B) At least one of the predictors is useful in explaining Y. C) The model is of no use in predicting the selling prices of houses. D) The estimates were based on a sample of 19 houses.

28) A realtor is trying to predict the selling price of houses in Greenville (in thousands of dollars) as a function of Size (measured in thousands of square feet) and whether or not there is a fireplace ( FP is 0 if there is no fireplace, 1 if there is a fireplace). Part of the regression output is provided below, based on a sample of 20 homes. Some of the information has been omitted. Variable

Coefficients

Intercept Size

128.93746

6.47601954

Standard Error 2.6205302 1.2072436 1.9803612

t-Statistic

P-value

49.203 11.439

8.93E-20 2.09E-09

3.27

0.004512

Which statement is supported by the regression output? A) At α = .05, FP is not a significant predictor in a two-tailed test. B) A fireplace adds around $6,476 to the selling price of the average house. C) A large house with no fireplace will sell for more than a small house with a fireplace. D) FP is a more significant predictor thanSize.

29)

A log transformation might be appropriate to alleviate which problem(s)?

Version 1

A) heteroscedastic residuals B) multicollinearity C) autocorrelated residuals D) insignificant residuals

30) is

A useful guideline in determining the extent of collinearity in a multiple regression model

A) Sturges’ Rule. B) Klein’s Rule. C) Occam’s Rule. D) Pearson’s Rule.

31)

In a multiple regression, all of the following are true regarding residuals except

A) their sum always equals zero. B) they are the differences between observed and predicted values of the response variable. C) they may be used to detect multicollinearity. D) they may be used to detect heteroscedasticity.

Version 1

32)

The residual plot below suggests which violation(s) of regression assumptions?

A) autocorrelation B) heteroscedasticity C) nonnormality D) multicollinearity

33)

Which isnot a standard criterion for assessing the usefulness of a regression model?

A) logic of causation B) overall fit C) degree of collinearity D) binary predictors

34)

If the standard error is 12, the width of a quick prediction interval for Y is

A) ±15. B) ±24. C) ±19. D) impossible to determine without an F table.

Version 1

35)

Which is a characteristic of the variance inflation factor (VIF)?

A) It is insignificant unless the corresponding t statistic is significant. B) It reveals collinearity rather than multicollinearity. C) It measures the degree of significance of each predictor. D) It indicates the predictor’s degree of multicollinearity.

36) Which statement best describes this regression where Y = highway miles per gallon (MPG) in 91 cars? R2

0.499

Adjusted R2 R Standard Error Source Regression Residual

0.444 0.707 4.019 SS 1,305.7251 1,308.3848

n k Dependent Variable df MS 9 145.0806 81 16.1529

Total

2,614.1099

91 9 HwyMPG F p-value 8.98 .0000

A) Regression is statistically significant but with large error in the MPG predictions. B) Regression is statistically significant and has quite small MPG prediction errors. C) Regression is not quite significant, but predictions should be very good. D) This is not a significant regression at any customary level ofα.

37) Based on these regression results, in your judgment which statement is most nearly correct ( Y = highway miles per gallon in 91 cars)? R2

0.499

Adjusted R2 R

0.444 0.707

Version 1

n k

91 9

Standard Error Source Regression Residual

4.019 SS 1,305.7251 1,308.3848

Dependent Variable df MS 9 145.0806 81 16.1529

Total

2,614.1099

HwyMPG F p-value 8.98 .0000

A) The number of predictors is rather small. B) Some predictors are not contributing much. C) Prediction intervals would be fairly narrow in terms of MPG. D) The overall model lacks significance and/or predictive power.

38)

In the following regression, which are the three best predictors?

Variables Intercept NumCyl HPMax ManTran Length Wheelbase Width RearStRm Weight Domestic

Coefficients 9.8080 −1.6804 −0.0369 0.2868 0.1109 −0.0701 0.4079 −0.0085 −0.0025 −1.2291

Standard Error 16.9900 0.5757 0.0140 1.2802 0.0601 0.1714 0.2922 0.2018 0.0020 1.1391

t (df = 81) 0.577 −2.919 −2.630 0.224 1.845 −0.409 1.396 −0.042 −1.266 −1.079

p-value .5654 .0045 .0102 .8233 .0686 .6836 .1665 .9666 .2090 .2838

A) ManTran, Wheelbase, RearStRm B) ManTran, Length, Width C) NumCyl, HPMax, Length D) Cannot be ascertained from the given information

39)

In the following regression, which are the two best predictors?

Variables Intercept

Version 1

Coefficients 9.8080

Standard Error 16.9900

NumCyl HPMax ManTran Length Wheelbase Width RearStRm Weight Domestic

−1.6804 −0.0369 0.2868 0.1109 −0.0701 0.4079 −0.0085 −0.0025 −1.2291

0.5757 0.0140 1.2802 0.0601 0.1714 0.2922 0.2018 0.0020 1.1391

A) NumCyl, HpMax B) Intercept, NumCyl C) NumCyl, Domestic D) ManTran, Width

40) In the following regression ( n = 91), which coefficients differ from zero in a two-tailed test at α = .05? Confidence Interval Variables Intercept NumCyl HPMax ManTran Length Wheelbase Width RearStRm Weight Domestic

Coefficients 9.8080 −1.6804 −0.0369 0.2868 0.1109 −0.0701 0.4079 −0.0085 −0.0025 −1.2291

95% lower −23.9968 −2.8260 −0.0648 −2.2604 −0.0087 −0.4111 −0.1735 −0.4100 −0.0064 −3.4955

95% upper 43.6129 −0.5349 −0.0090 2.8341 0.2305 0.2709 0.9893 0.3931 0.0014 1.0374

A) NumCyl, HPMax B) Intercept, ManTran C) Intercept, NumCyl, Domestic D) Intercept, Domestic

Version 1

41)

Based on the following regression ANOVA table, what is the R2?

Source Regression Residual

df 4 45

SS 1793.2356 2695.0996

Total

4488.3352

MS 448.3089 59.8911

F 7.48540

A) .1336 B) .6005 C) .3995 D) insufficient information to answer

42)

Based on the following regression ANOVA table, what is the MS for the residuals?

Source Regression Residual

df 4 45

SS 1793.2356 2695.0996

Total

4488.3352

MS 448.3089

F 7.48540

A) 2695.0996 B) 59.8911 C) 673.7749 D) insufficient information to answer

43) In the following regression, which statement best describes the degree of multicollinearity? Variables Intercept

Version 1

Coefficients 9.8080

Standard Error 16.9900

t (df = 81) 0.577

pvalue .5654

VIF

NumCyl HPMax ManTran Length Wheelbase Width RearStRm Weight Domestic

−1.6804 −0.0369 0.2868 0.1109 −0.0701 0.4079 −0.0085 −0.0025 −1.2291

0.5757 0.0140 1.2802 0.0601 0.1714 0.2922 0.2018 0.0020 1.1391

−2.919 −2.630 0.224 1.845 −0.409 1.396 −0.042 −1.266 −1.079

.0045 .0102 .8233 .0686 .6836 .1665 .9666 .2090 .2838

3.159 3.068 2.105 4.339 7.553 6.857 2.015 7.670 1.825

A) There is very little evidence of multicollinearity. B) There is much evidence of multicollinearity. C) Only NumCyl and HPMax are collinear. D) Only ManTran and RearStRm are collinear.

The relationship of Y to four other variables was established as Y = 12 + 3 X1 − 5 X2 + 7 44) X3 + 2 X4. When X1 increases 5 units and X2 increases 3 units, while X3 and X4 remain unchanged, what change would you expect in your estimate of Y?

A) Decrease by 15. B) Increase by 15. C) No change. D) Increase by 5.

Version 1

45) Does the picture below show strong evidence of heteroscedasticity against the predictor Wheelbase?

A) Yes, there is strong evidence of heteroscedasticity. B) No, the plot appears mostly random againstWheelbase. C) We need a probability plot to answer. D) We need VIF statistics to answer.

46)

Which is not a correct way to find the coefficient of determination?

A) SSR/ SSE B) SSR/ SST C) 1 − SSE/ SST D) SSR/(SSR + SSE)

47)

Which is the correct way to find the coefficient of determination?

Version 1

A) SSR/SSE B) SSE/SSR C) 1 −SSE/SST D) SSE/SST

48)

If SSR = 3600, SSE = 1200, and SST = 4800, then R2 is

A) .5000. B) .7500. C) .3333. D) .2500.

49)

Which statement is incorrect?

A) Positive autocorrelation results in too many centerline crossings in the residual plot over time. B) The R2 statistic can only increase (or stay the same) when you add more predictors to a regression. C) If the F-statistic is insignificant, the t statistics for the predictors also are insignificant at the same α. D) A regression with 60 observations and 5 predictors does not violate Evans’ Rule.

50)

Which statement about leverage is incorrect?

A) Leverage refers to an observation’s distance from the mean of X. B) If n = 40 and k = 4 predictors, a leverage statistic of .15 would indicate high leverage. C) If n = 180 and k = 3 predictors, a leverage statistic of .08 would indicate high leverage. D) A high leverage observation could artificially increase the value ofR2.

Version 1

51)

Which statement is incorrect?

A) Binary predictors shift the intercept of the fitted regression. B) If a qualitative variable has c categories, we would use only c − 1 binaries as predictors. C) A binary predictor has the same t test as any other predictor. D) If there is a binary predictor ( X = 0, 1) in the model, the residuals may not sum to zero.

52)

Heteroscedasticity of residuals in regression suggests that there is

A) nonconstant variation in the errors. B) multicollinearity among the predictors. C) nonnormality in the errors. D) lack of independence in successive errors.

53)

If you rerun a regression, omitting a predictor X5, which would be unlikely? 2

A) The new R will decline if X5 was a relevant predictor. B) The new standard error will increase if X5 was a relevant predictor. C) The remaining estimated β’s will change if X5 was collinear with other predictors. D) The numerator degrees of freedom for the F test will increase.

54)

In a multiple regression, which is an incorrect statement about the residuals?

Version 1

A) They may be used to test for multicollinearity. B) They are differences between observed and estimated values of Y. C) Their sum will always equal zero. D) They may be used to detect heteroscedasticity.

55)

Which of the following is not a characteristic of the F distribution?

A) It is a continuous distribution. B) It uses a test statistic Fcalc that can never be negative. C) Its degrees of freedom vary, depending on α. D) It is used to test for overall significance in a regression.

56) Which of the following would be most useful in checking the normality assumption of the errors in a regression model?

A) the t statistics for the coefficients B) the F-statistic from the ANOVA table C) the histogram of residuals D) the VIF statistics for the predictors

57) The regression equation Salary = 25,000 + 3200 YearsExperience + 1400 YearsCollege describes employee salaries at Axolotl Corporation. The standard error is 2600. John has 10 years’ experience and 4 years of college. His salary is $66,500. What is John’s standardized residual?

A) −1.250 B) −0.240 C) +0.870 D) +1.500

Version 1

58) The regression equation Salary = 28,000 + 2700 YearsExperience + 1900 YearsCollege describes employee salaries at Ramjac Corporation. The standard error is 2400. Mary has 10 years’ experience and 4 years of college. Her salary is $58,350. What is Mary’s standardized residual (approximately)? A) −1.150 B) +2.007 C) −1.771 D) +1.400

59) Which Excel function will give the p-value for overall significance if a regression has 75 observations and 5 predictors and gives an F test statistic Fcalc = 3.67?

A) =F.INV(.05, 5, 75) B) =F.DIST(3.67, 4, 74) C) =F.DIST.RT(3.67, 5, 69) D) =F.DIST(.05, 4, 70)

60) The ScamMore Energy Company is attempting to predict natural gas consumption for the month of January. A random sample of 50 homes was used to fit a regression of gas usage (in CCF) using as predictors Temperature = the thermostat setting (degrees Fahrenheit) and Occupants = the number of household occupants. They obtained the following results: Variable Intercept Temperature Occupants

Coefficient 21.684 0.9142 2.244

Standard Error 4.122 0.2918 1.315

In testing each coefficient for a significant difference from zero (two-tailed test at α = .10), which is the most reasonable conclusion about the predictors?

Version 1

A) Temperature is highly significant; Occupants is barely significant. B) Temperature is not significant; Occupants is significant. C) Temperature is less significant than Occupants. D) Temperature is significant; Occupants is not significant.

61)

In a regression with 60 observations and 7 predictors, there will be

residuals.

A) 60 B) 59 C) 52 D) 6

62)

A regression with 72 observations and 9 predictors violates

A) Evans’ Rule. B) Klein’s Rule. C) Doane’s Rule. D) Sturges’ Rule.

63) The F test for ANOVA in a regression model with 4 predictors and 47 observations would have how many degrees of freedom?

A) (3, 44) B) (4, 46) C) (4, 42) D) (3, 43)

Version 1

64) In a regression with 7 predictors and 62 observations, degrees of freedom for a t test for each coefficient would use how many degrees of freedom?

A) 61 B) 60 C) 55 D) 54

65)

In a multiple regression with k independent variables, the standard error is

A) the sum of the squared residuals. B) the sum of the residuals. C) the sum of the residuals divided by n − k − 1. D) the square root of SSE divided by n − k − 1.

66)

If the standard error is 18, an approximate prediction interval width for Y is

A) ±36. B) ±24. C) ±18. D) impossible to determine without an F table.

For a given set of values for x1, x2, . . . , xk the confidence interval for the conditional 67) mean of Y is

A) narrower than the prediction interval for the individual Y value. B) wider than the prediction interval for the individual Y value. C) usually about the same as the prediction interval for the individual Y value. D) could be wider or narrower, depending on the magnitude ofY.

Version 1

68)

Which estimated multiple regression contains an interaction term?

A) y = 47 − 12x1 + 8x1x2 − 5x2 B) y = 47 − 12x1 + 8x12 − 5x2 + 25x22 C) y = 47 − 12x12 + 5x22 D) y = 47 − 12x12 + 4x2 + 5x23

69)

Which estimated multiple regression contains an interaction term?

A) y = − 92 + 6x12 − 12x22 B) y = 47 − 18x1 − 3x12 + 6x2 + 36x22 C) y = 88 + 11x1 + 7x1x2 + 5x2 D) y = 47 − 12x12 + 4x2 + 5x23

70)

Which estimated multiple regression allows a test for nonlinearity?

A) y = 47 − 12x1 + 8x1x2 − 5x2 B) y = 47 − 12x1 + 8x12 − 5x2 + 25x22 C) y = 47 − 12x1 + 5x2 + 13x3 D) y = 47 − 12x1 + 4x2 + 5x2

71)

Which estimated multiple regression has nonlinearity tests?

Version 1

A) y = − 92 − 5x1 + 6x12 + 18x2 − 12x22 B) y = 47 − 18x1 − 3x2 + 6x3 + 36x4 C) y = 88 + 11x1 + 7x1x2 + 5x2 D) y = 47 − 12x12 + 4x2 + 5x23

72)

Simple tests for nonlinearity in a regression model can be performed by

A) squaring the standard error. B) including squared predictors. C) deleting predictors one at a time. D) multiplying two predictors.

73) The regression equation Salary = 35,000 + 3500 YearsExperience + 1200 YearsCollege describes employee salaries at Streeling Research Labs. The standard error is 2500. Doris has 20 years’ experience and 4 years of college. Her salary is $113,000. What is Doris’s standardized residual?

A) +1.28 B) −0.24 C) −1.28 D) +3.20

74) The regression equation Salary = 45,000 + 1500 YearsExperience + 2800 YearsCollege describes employee salaries at Terminus Fissile Labs. The standard error is 2500. Lars has 15 years’ experience and 4 years of college. His salary is $70,500. If this regression is valid, we conclude that

Version 1

A) Lars is underpaid, but is not an outlier. B) Lars is underpaid, and his salary is an outlier. C) Lars is overpaid, but is not an outlier. D) Lars is overpaid, and his salary is an outlier.

75) In a regression with n = 50 observations and k = 3 predictors, the criterion for high leverage is

A) hi ≥ .33. B) hi ≥ .25. C) hi ≥ .21. D) hi ≥ .16.

76) In a regression with n = 100 observations and k = 5 predictors, the criterion for high leverage is

A) hi ≥ .06. B) hi ≥ .12. C) hi ≥ .18. D) hi ≥ .24.

77)

A high leverage observation will have

A) an unusual value of the observed Y. B) unusual values of one or more X values. C) a large standardized residual. D) high correlations between the X values.

Version 1

78)

An observation with extreme values in one or more independent variables (predictors)

A) has reduced influence on the estimated coefficients. B) has increased influence on the estimated coefficients. C) causes an overstated estimate of the standard error. D) leads to high correlations between the X values.

79)

A logistic regression is appropriate when

A) the dependent variable is binary (0, 1). B) an independent variable is binary (0, 1). C) the dependent variable is log( Y). D) the independent variables have the form log( X).

80)

When the dependent variable is binary (0 or 1), we need

A) stepwise regression. B) data transformation to improve conditioning. C) logistic regression. D) best subsets regression.

81) When the predictor units of measurement differ greatly in magnitude, which action might be useful?

Version 1

A) stepwise regression to detect which predictors are best B) decimal transformations to improve data conditioning C) logistic regression to produce probability predictions D) best subsets regression to find the best model

82) When we have no prior guidance on which combination of predictors is best, we might consider

A) log transformations. B) decimal transformations. C) logistic regression. D) best subsets regression.

83)

To find which predictors are most helpful in increasing R2, we might consider

A) log transformations. B) stepwise regression. C) logistic regression. D) nonlinear regression.

84)

The forward selection method of stepwise regression

A) starts with all the predictors in the model and deletes the weaker ones. B) adds predictors one at a time starting with the best single predictor. C) runs all possible models and then chooses the best fitting one. D) requires nonlinear estimation using maximum likelihood.

Version 1

85)

The backward elimination of stepwise regression

A) sometimes misses the best model for a given number of predictors. B) adds predictors one at a time starting with the best single predictor. C) runs all possible models and then chooses the best one. D) requires nonlinear estimation using maximum likelihood.

86)

Which is not true of the logistic regression model?

A) It is nonlinear. B) It can best be fitted using the maximum likelihood method. C) Its predictions are either 0 or 1. D) It cannot yield predictions greater than 1.

87)

In regression, the dependent variable is referred to as the response variable. ⊚ ⊚

88)

In regression, the dependent variable is referred to as the explanatory variable. ⊚ ⊚

89)

true false

In multiple regression there can be multiple dependent variables. ⊚ ⊚

Version 1

true false

90)

In multiple regression the dependent variable can be binary. ⊚ ⊚

true false

If a regression model’s F test statistic is Fcalc = 43.82, we could say that the explained 91) variance is approximately 44 percent. ⊚ ⊚

92)

true false

In a regression, the model with the best fit is preferred over all other models. ⊚ ⊚

true false

93) A common misinterpretation of the principle of Occam’s Razor is that a simple regression model (rather than a multiple regression model) is always best. ⊚ ⊚

true false

94) A predictor whose pairwise correlation with Y is near zero can still have a significant tvalue in a multiple regression when other predictors are included. ⊚ ⊚

true false

95) The F statistic in a multiple regression is significant if at least one of the predictors has a significant t statistic at a given α.

Version 1

⊚ ⊚

96)

true false

R2adj can exceed R2 if there are several weak predictors. ⊚ ⊚

true false

97) A binary (categorical) predictor should not be used along with nonbinary (numerical) predictors. ⊚ ⊚

true false

98) In a multiple regression with three predictors in a sample of 25 U.S. cities, we would use F3,21 in a test of overall significance. ⊚ ⊚

99)

true false

Evans’ Rule says that if n = 50 you need at least five predictors to have a good model. ⊚ ⊚

true false

100) Evans' Rule says that if you have five predictors then you should have at leastn = 50 to have a good model. ⊚ ⊚

Version 1

true false

101) The model Y = β0 + β1 X + β2 X cannot be estimated by Excel because of the nonlinear term. ⊚ true ⊚ false

102)

The random error term in a regression model reflects all factors omitted from the model. ⊚ ⊚

true false

103) If the probability plot of residuals resembles a straight line, the residuals show a fairly good fit to the normal distribution. ⊚ ⊚

true false

104) Confidence intervals for Y may be unreliable when the residuals are not normally distributed. ⊚ ⊚

105)

true false

A negative estimated coefficient in a regression usually indicates a weak predictor. ⊚ ⊚

Version 1

true false

106) For a certain firm, the regression equation Bonus = 2,000 + 257 Experience + 0.046 Salary describes employee bonuses with a standard error of 125. John has 10 years’ experience, earns $50,000, and earned a bonus of $7,000. John is an outlier. ⊚ ⊚

107)

There is one residual for each predictor in the regression model. ⊚ ⊚

108)

true false

A parsimonious model is one with many weak predictors but a few strong ones. ⊚ ⊚

111)

true false

The effect of a binary predictor is to shift the regression intercept. ⊚ ⊚

110)

true false

If R2 and R2adj differ greatly, we should probably add a few predictors to improve the fit. ⊚ ⊚

109)

true false

The F statistic and its p-value give a global test of significance for a multiple regression. ⊚ ⊚

Version 1

true false

112) In a regression model of student grades, we would code the nine categories of business courses taken (ACC, FIN, ECN, MGT, MKT, MIS, ORG, POM, QMM) by including nine binary (0 or 1) predictors in the regression. ⊚ ⊚

true false

113) A disadvantage of Excel’s Data Analysis regression tool is that it expects the independent variables to be in a block of contiguous columns, so you must delete a column if you want to eliminate a predictor from the model. ⊚ ⊚

true false

114) A disadvantage of Excel’s regression is that it does not give as much accuracy in the estimated regression coefficients as a package like Minitab. ⊚ ⊚

true false

115) Nonnormality of the residuals from a regression can best be detected by looking at the residual plots against the fitted Y values. ⊚ ⊚

116)

true false

A high variance inflation factor (VIF) indicates a significant predictor in the regression. ⊚ ⊚

Version 1

true false

117)

Autocorrelation may be detected by looking at a plot of the residuals against time. ⊚ ⊚

118)

true false

A widening pattern of residuals as X increases would suggest heteroscedasticity. ⊚ ⊚

true false

119) Plotting the residuals against a binary predictor ( X = 0, 1) reveals nothing about heteroscedasticity. ⊚ ⊚

true false

120) The regression equation Bonus = 2,812 + 27 Experience + 0.046 Salary says that Experience is the most significant predictor of Bonus. ⊚ ⊚

121)

true false

A multiple regression with 60 observations should not have 13 predictors. ⊚ ⊚

Version 1

true false

122) A regression of Y using four independent variables X1, X2, X3, X4 could also have up to four nonlinear terms ( X2) and six simple interaction terms ( Xj Xk) if you have enough observations to justify them. ⊚ ⊚

123)

true false

When autocorrelation is present, the estimates of the coefficients will be unbiased. ⊚ ⊚

true false

124) If the residuals in your regression are nonnormal, a larger sample size might help improve the reliability of confidence intervals for Y. ⊚ ⊚

125)

true false

Multicollinearity can be detected from t tests of the predictor variables. ⊚ ⊚

true false

126) When multicollinearity is present, the regression model is of no use for making predictions. ⊚ ⊚

true false

127) Autocorrelation of the residuals may affect the reliability of the t-values for the estimated coefficients of the predictors X1, X2, . . . , Xk.

Version 1

⊚ ⊚

true false

128) The first differences transformation might be tried if autocorrelation is found in a timeseries data set. ⊚ ⊚

true false

129) Statisticians who work with cross-sectional data generally do not anticipate autocorrelation. ⊚ ⊚

true false

130) The ill effects of heteroscedasticity might be mitigated by redefining totals (e.g., total number of homicides) as relative values (e.g., homicide rate per 100,000 population). ⊚ ⊚

131)

Nonnormal residuals lead to biased estimates of the coefficients in a regression model. ⊚ ⊚

132)

true false

A large VIF (e.g., 10 or more) would indicate multicollinearity. ⊚ ⊚

Version 1

true false

133)

Heteroscedasticity exists when all the errors (residuals) have the same variance. ⊚ ⊚

134)

Multicollinearity refers to relationships among the independent variables. ⊚ ⊚

135)

true false

A squared predictor is used to test for nonlinearity in the predictor’s relationship to Y. ⊚ ⊚

true false

136) Nonnormality of residuals is not usually considered a major problem unless there are outliers. ⊚ ⊚

true false

137) In the fitted regression Y = 12 + 3 X1 − 5 X2 + 27 X3 + 2 X4 the most significant predictor is X3. ⊚ ⊚

true false

138) Given that the fitted regression is Y = 76.40 − 6.388 X1 + 0.870 X2, the standard error of b1 is 1.453, and n = 63, at α = .05, we can conclude that X1 is a significant predictor of Y. Version 1

⊚ ⊚

139)

Unlike other predictors, a binary predictor has a t-value that is either 0 or 1. ⊚ ⊚

140)

true false

Thet statistics show the ratio of an estimated coefficient to its standard error. ⊚ ⊚

true false

141) In a multiple regression with five predictors in a sample of 56 U.S. cities, we would use F5,50 in a test of overall significance. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 13_7e_Doane 1) B 2) C 3) D 4) C 5) B 6) D 7) A 8) B 9) C 10) D 11) C 12) B 13) B 14) A 15) A 16) C 17) D 18) C 19) C 20) A 21) C 22) D 23) C 24) B 25) B 26) D Version 1

27) B 28) B 29) A 30) B 31) C 32) B 33) D 34) B 35) D 36) A 37) B 38) C 39) A 40) A 41) C 42) B 43) B 44) C 45) B 46) A 47) C 48) B 49) A 50) B 51) D 52) A 53) D 54) A 55) C 56) C Version 1

57) D 58) C 59) C 60) A 61) A 62) A 63) C 64) D 65) D 66) A 67) A 68) A 69) C 70) B 71) A 72) B 73) A 74) B 75) D 76) B 77) B 78) B 79) A 80) C 81) B 82) D 83) B 84) B 85) A 86) C Version 1

87) TRUE 88) FALSE 89) FALSE 90) FALSE 91) FALSE 92) FALSE 93) TRUE 94) TRUE 95) TRUE 96) FALSE 97) FALSE 98) TRUE 99) FALSE 100) TRUE 101) FALSE 102) TRUE 103) TRUE 104) TRUE 105) FALSE 106) FALSE 107) FALSE 108) FALSE 109) TRUE 110) FALSE 111) TRUE 112) FALSE 113) TRUE 114) FALSE 115) FALSE 116) FALSE Version 1

117) TRUE 118) TRUE 119) FALSE 120) FALSE 121) TRUE 122) TRUE 123) TRUE 124) TRUE 125) TRUE 126) FALSE 127) TRUE 128) TRUE 129) TRUE 130) TRUE 131) FALSE 132) TRUE 133) FALSE 134) TRUE 135) TRUE 136) TRUE 137) FALSE 138) TRUE 139) FALSE 140) TRUE 141) TRUE

Version 1

CHAPTER 14 1)

The time-series model Y = T × C × S × I

A) is an additive model. B) is a multiplicative model. C) is an exponential model. D) is a polynomial model.

2) If we fit a linear trend to 10 observations on time-series data that are growing exponentially, then it is most likely that

A) the fitted trend will be too high at t = 1 and t = 10. B) the fitted trend will be too low in the middle. C) the forecasts (if extrapolated) will be too low. D) the residuals will show a pattern like −−− + + + + −−−.

The implied turning point (peak or trough) of yt = 516 − 42 t +3 t would be in which 3) period? Hint: Use calculus to solve for the value of t that would maximize or minimize yt.

A) t = 7 B) t = −7 C) t = 6 D) t = −42

In the model yt = 516 − 42 t + 3 t2 the turning point

Version 1

A) is a peak. B) is a trough. C) could be either a peak or a trough. D) is neither a peak nor a trough.

A computer analysis reveals that the best-fitting trend model is yt = 4.12 e0.987 t. The trend 5) was fitted using year-end common stock prices for Melodic Kortholt Outlet for the last six years. The R2 is .8571. Which conclusion is not supportable?

A) The absolute annual growth (in dollars per share) is increasing. B) Few investments could match the astounding growth rate. C) At the end of year 3, the stock price would be nearly $80. D) The exponential model is inappropriate for financial data.

A computer analysis reveals that the best-fitting trend model isyt = 4.12e0.987t. The trend 6) was fitted using year-end common stock prices for Melodic Kortholt Outlet for the last six years. TheR2 is .8571. What is the forecast for year seven’s stock price?

A) $1537 B) $4125 C) $28 D) $572

Suppose the estimated quadratic model yt = 500 + 20 t − t2 is the best-fitting trend of sales 7) of XYZ Incorporated using data for the past 20 years ( t = 1, 2, . . . , 20). Which statement is incorrect?

Version 1

A) Sales are increasing by about 20 units per year. B) The turning point would be in period 10. C) Latest year sales are no better than in year zero. D) The trend was higher in year 10 than in year 20.

Which statement is most defensible regarding the time series shown below?

A) There appears to be strong seasonality. B) There appears to be a six-month seasonal cycle. C) The trend appears to be exponential. D) The quadratic trend would be required.

If the trend model yt = a + bt + ct2 is fitted to a time series, we would get A) R2 that could be lower than the linear model. B) R2 that could be either higher or lower than the linear model. C) R2 that is at least as high as the linear model. D) no R2 for this type of model because it is nonlinear.

Version 1

10)

The fitted annual sales trend is yt = 187 e−.047 t. The sales forecast for year 5 would be

A) 236.9. B) 178.7. C) 175.3. D) 147.8.

11)

The fitted annual sales trend is yt = 227 e.037 t. The values of yt are A) rising by an increasing amount each period. B) rising by a declining amount each period. C) declining by a declining amount each period. D) declining by an increasing amount each period.

12)

If a fitted trend equation is yt = 120 − 40 t + 2.5 t2, then the turning point will be

A) a peak in period 40. B) a trough in period 5. C) a peak in period 4. D) a trough in period 8.

13)

If a fitted trend equation isyt = 120 − 40t + 2.5t2, then the forecast for period 5 will be A) −20. B) 0. C) −17.5. D) 10.

Version 1

14)

If the fitted annual trend for a stock price is yt = 27 e0.213 t, then

A) the slow growth rate is not very attractive. B) the stock price seems to be approaching an asymptote. C) the stock is probably undervalued in today’s markets. D) the stock would more than double every four years.

15)

What is the approximate slope of a linear trend for the value of Bob’s beer can collection?

A) −25 B) −50 C) −15 D) −10

Version 1

16)

Which trend would you choose to forecast the 2013 value of Bob’s beer can collection?

A) Linear model is preferred. B) Exponential model is preferred. C) Neither model is appropriate. D) Either model works—they are equivalent.

17)

Which trend would you choose to forecast the 2013 value of Bob’s beer can collection?

A) Exponential model is preferred. B) Quadratic model is preferred. C) They are equivalent. D) Neither model is appropriate.

Version 1

18)

Might it be acceptable to use exponential smoothing to forecast 2010 for Bob’s data?

A) No, under no circumstances. B) Yes, if you use only the most recent 10 years. C) Yes, if you need a long-term forecast (e.g., to 2020). D) No, because the data appear to be erratic.

19)

Which trend would you choose to forecast the number of tractors sold in 2010?

A) Linear model is best. B) Polynomial model is best. C) Either gives equivalent forecasts. D) Neither model is appropriate.

Version 1

20)

Which trend would you choose to forecast the number of water damage claims in 2010?

A) Exponential model is best. B) Polynomial model is best. C) Models give equivalent forecasts. D) Neither model is appropriate.

21) A quadratic trend equation yt = 900 + 80 t − 5 t2 was fitted to a company’s sales. This result implies that the sales trend

A) hit a peak in period 8. B) hit a peak in period 5. C) hit a trough in period 8. D) hit a trough in period 5.

22)

If we fit a linear trend to data that are growing exponentially, which is least likely?

A) The fitted trend will be too low at the beginning and end. B) The fitted trend will be too high in the middle. C) The forecasts (if extrapolated) will be too low. D) The fit will be poor to the most recent data.

Version 1

23)

For the fitted time-series trend model yt = 9.23 e−0.0867t, it is correct to say that

A) the series is growing by 9.23 percent. B) the series is growing by 8.67 percent. C) the model probably shows a low R2. D) the time series would be declining.

24)

If a trend is given by yt = aebt, then A) the fitted trend value in period 0 is b. B) the trend is exponentially increasing. C) the trend is exponentially decreasing. D) the trend is increasing if b > 0 and decreasing if b < 0.

25) Suppose you fit a (linear or nonlinear) trend regression to a monthly time series and discover that the R2 is only 18 percent. The best conclusion is that

A) adding seasonal factors might make things worse. B) fitting a seasonal component could raise the R2. C) there is no seasonality in the time series. D) the overall trend is probably negative.

26) A trend line has been fitted to a company’s annual sales. The trend is given by yt = 50 + 5 t, where t is the time index ( t = 1, 2, . . . , n) and yt is annual sales (in millions of dollars). The implication of this trend line is that sales are expected to increase

Version 1

A) by $5 million every year. B) by exactly 5 percent every year. C) by an average of 5 percent per year. D) by an average of $5 million per year.

27) Consider the following linear trend equation of an industry’s sales: yt = 120 + 12 t, where t is measured in years and sales are measured in millions of dollars. Which is the most reasonable conclusion?

A) We would forecast that sales will increase $12 million in the next year. B) We would forecast that sales will increase 12 percent in the next year. C) On the average, sales will increase 12/(120 + 12 × 10) = 0.05, or 5 percent next year. D) The year-to-year change will depend on the value of t.

28) In a multiplicative model, if the seasonal factor is 1.15 for a particular season, then we expect that the time series in that season would be (other things being equal)

A) 115 percent above the trend. B) 115 percent below the trend. C) 15 percent above the trend. D) 15 percent below the trend.

29) A quadratic trend equation was estimated from monthly sales of trucks in the United States from July 2006 to July 2011. The estimated trend is yt = 106 + 1.03 t + 0.048 t2, where yt units are in thousands. From this trend, how many trucks would be sold in July 2012?

Version 1

A) about 308,419 B) about 524,889 C) about 436,982 D) about 223,831

30) A quadratic trend equation yt = 900 + 30 t − 2.5 t2 was fitted to a company’s sales. This result implies that the sales trend

A) hit a maximum in period t = 30. B) hit a maximum in period t = 6. C) hit a minimum in period t = 5. D) hit a minimum in period t = 6.

31)

The fitted sales trend over the last 12 years is yt = 14.7 e0.063 t. We can say that A) sales grew (on average) at 63 percent per annum. B) sales in year 10 would be about 39. C) a continuously compounded model was used. D) sales in year 1 were 14.7.

32)

Which data would be measured over an interval of time as opposed to at a point in time?

A) Toyota’s accounts receivable on December 31, 2017 B) Costco’s sales for fiscal year 2017 C) the Canadian unemployment rate on December 1, 2017 D) the closing price of Wal-Mart’s stock last Friday

Version 1

33)

Which data would be measured over an interval of time as opposed to at a point in time?

A) Toyota’s total revenue for fiscal 2017 B) Toyota’s salaried employee head count at the end of June 2017 C) Toyota’s short-term indebtedness at the end of fiscal 2017 D) Toyota’s inventory of unsold vehicles on December 31, 2017

34)

Which is a characteristic of an additive (as opposed to multiplicative) time-series model?

A) It is appropriate for financial data over a longer time period. B) It is appropriate for rapidly growing financial data. C) It is appropriate for data that vary by an order of magnitude. D) It is appropriate for short-term data with a steady dollar growth.

35)

If yt = 50 e0.07 t, which forecast for period 10 is correct? A) 100.7 B) 90.7 C) 80.7 D) 70.7

36)

If yt = 544 e0.07 t, which forecast for period 7 is correct? A) 989 B) 888 C) 678 D) 589

Version 1

37)

If yt = 256 e−0.07 t, which forecast for period 6 is correct?

A) 390 B) 203 C) 179 D) 168

38) MegaStat’s seasonal factor of 1.073 applied to a monthly trend forecast of 125.820 would give which seasonally adjusted forecast?

A) 135.005 B) 126.893 C) 137.044 D) 124.228

39)

Which statement is correct regarding forecasting using an exponential smoothing model?

A) A model with low α is more responsive to new data than a model with high α. B) Increasing α will typically increase the forecast accuracy. C) As α increases, more weight is put on recent data. D) When data have an upward trend, the forecasts will have an upward bias.

40) Which of the following best describes the decomposition modeling approach to forecasting?

Version 1

A) The values of certain variables are used to predict the values of others. B) Series are separated into trend, seasonal, irregular, and cyclical components. C) Forecasts are based on an average of recent values. D) Sophisticated models such as regression with binaries are preferred.

41) Which of the following is the least useful time-series forecasting model when there is a strong upward trend in the data?

A) estimated exponential trend model B) a five-period centered moving average C) exponential smoothing with a high α D) regression model with trend and seasonal binaries

42)

Which model assumes a constant percentage rate of growth?

A) linear B) quadratic C) cubic D) exponential

43)

The compound growth rate in the fitted trend equation yt = 228 e −.0982 t is

A) 98.2 percent. B) −9.82 percent. C) 198.2 percent. D) 228 percent.

Version 1

44)

Which statement is most nearly correct regarding time-series trend models?

A) The quadratic model is best for a series that is growing by a constant percentage. B) A linear model may yield a higher R2 than a quadratic model. C) The exponential model is rarely used for financial data. D) The exponential model would be linear if we take the natural log of yt.

45)

Which is a time series?

A) last year’s GDP in 27 developing countries B) year-end unemployment rates in the United States, 2000–2010 C) passenger miles flown by each of 10 major airlines in 2010 D) the number of "hits" on each of 10 websites yesterday

46)

Which is not a component of a time series?

A) trend B) seasonal C) irregular D) linearity

47)

Which component of a time series typically occurs over multiple years? A) trend B) seasonal C) irregular D) cycle

Version 1

48) The "up-and-down" component of a time series that represents periods of prosperity followed by recession over extended periods of time longer than one year is called

A) trend variation. B) seasonal variation. C) cyclical variation. D) irregular variation.

49)

Fluctuations caused by strikes and floods are

A) cyclical fluctuations. B) irregular fluctuations. C) residual fluctuations. D) seasonal fluctuations.

50)

The four components of a time series are which of the following?

A) cycle, season, month, day B) month, cycle, seasonal, irregular C) cycle, seasonal, irregular, regular D) seasonal, cycle, irregular, trend

51)

Which measure of fit is measured in the same units as Y?

A) MAPE B) MAD C) R2 D) MSD

Version 1

52)

The fitted annual sales trend is Yt = 187.3 e−.047 t. On average, sales are

A) rising by an increasing absolute amount each year. B) rising by a declining absolute amount each year. C) falling by a declining absolute amount each year. D) falling by an increasing absolute amount each year.

53)

If Y1 = 116 and Y7 = 255, which is the simple index number for period 7 (denoted I7)?

A) 215.3 B) 219.8 C) 222.7 D) 242.4

54)

Concerning a seasonal index for monthly data, which statement is incorrect?

A) A multiplicative index value of 1.000 indicates no seasonal deviation from trend. B) Coefficients on seasonal binary predictors (additive indexes) are adjusted so they always sum to 12. C) To make forecasts, we multiply the trend by each month’s seasonal index. D) Seasonal indexes are obtained by the process called decomposition of a time series.

55)

Which statement is correct for a simple index number?

Version 1

A) For the base year, the index is set to 0.000. B) We cannot use index numbers to compare two time series measured in different units. C) The simple relative index for period t = 5 is calculated as Y5/ Y1. D) Weighted index numbers have few practical applications because of their complexity.

56)

Which is a time series?

A) The M1 component of the money supply for the United States ( n = 20 quarters). B) The unemployment rates for the U.S. states ( n = 50 states). C) The gross domestic product for E.U. members ( n = 27 nations). D) The inflation rate for housing in U.S. metropolitan areas ( n = 46 cities).

57)

To initialize the forecasts in an exponential smoothing process, it is acceptable to

A) use the average of the first six observed data values. B) use the most recent data value in the observed data. C) apply the smoothing constant α to the mean of the data. D) ask a panel of experts to make a guess at the initial forecast.

58)

If a fitted trend equation is yt = 220 − 40 t + 2.5 t2, which is the forecast for period 6?

A) 225 B) 70 C) 304 D) 110

59)

If a fitted trend equation is yt = 184 e−.047 t, which is the forecast for period 4?

Version 1

A) 195 B) 222 C) 152 D) 138

60)

If a fitted trend equation is yt = 816 e0.065 t, which is the forecast for period 7? A) 1286 B) 895 C) 944 D) 1018

61)

If a fitted trend equation is yt = 227 e−.098 t, which is the forecast for period 5?

A) 372 B) −87 C) −216 D) 139

62) Ft+1?

Using exponential smoothing, if Ft = 33, yt = 41, and α = .20, what is the new forecast

A) 34.6 B) 36.2 C) 38.1 D) 40.2

Version 1

63) Ft+1?

Using exponential smoothing, if Ft = 12, yt = 15, and α = .10, what is the new forecast

A) 14.1 B) 12.6 C) 12.3 D) 13.7

64) Ft+1?

Using exponential smoothing, if Ft = 220, yt = 240, and α = .20, what is the new forecast

A) 217 B) 224 C) 232 D) 243

65)

Which of the following measures of fit is unit free?

A) MAD (mean absolute deviation) B) SE (standard error) C) MSD (mean squared deviation) D) R2 (coefficient of determination)

66)

Which of the following measures of fit is expressed in the same units as yt?

A) SE (standard error) B) MAPE (mean absolute percent error) C) MSD (mean squared error) D) R2 (coefficient of determination)

Version 1

67)

Which of the following measures of fit is expressed in percent?

A) SE (standard error) B) MAPE C) MSD D) MAD

68)

For these data, what is the three-period centered moving average for period 4?

t yt

1 22

2 33

3 27

4 34

5 38

6 26

7 28

8 35

9 41

8 35

9 41

A) 33.33 B) 31.33 C) 33.00 D) 34.00

69)

For these data, what is the three-period trailing moving average for period 6?

t yt

1 22

2 33

3 27

4 34

5 38

6 26

7 28

A) 32.67 B) 31.33 C) 33.00 D) 34.67

Use the estimated regression equation yt = 448 + 12 t + 18 Qtr1 − 26 Qtr2 + 3 Qtr3 to 70) make a forecast for period 13. The regression model has three quarterly binaries (0 or 1). The model was fitted to 12 periods of quarterly data, starting with the first quarter. Version 1

A) 588 B) 476 C) 622 D) No forecast is possible without knowing R2.

The estimated regression equation is yt = 448 + 12 t + 18 Qtr1 − 26 Qtr2 + 3 Qtr3. The 71) regression model has three quarterly binaries. The model was fitted to 12 periods of quarterly data starting with the first quarter. Why is there no fourth quarterly binary for Qtr4?

A) Because the researcher made a mistake. (We must include a binary for each quarter.) B) Because it is unnecessary. (Its value is implied by the other three binaries.) C) Because the fourth quarter binary is assumed to be the same as the first quarter. D) Because there is no seasonality in the fourth quarter in most time series.

72)

Concerning a seasonal index for monthly data, which statement isincorrect?

A) An index value greater than 1.000 indicates that month tends to be greater than average. B) Monthly indexes can be negative but must sum to 12. C) An index value less than 1.000 indicates that month tends to be less than average. D) Seasonal indexes are obtained by the process called decomposition of a time series.

73) A multiplicative time-series model Y = T × C × S × I becomes an additive model if we take the logarithm of each side of the equation. ⊚ ⊚

Version 1

true false

74) A firm’s income statement contains data measured over a period of time, as opposed to being measured at a point in time. ⊚ ⊚

true false

75) A firm's income measured over a period of time would be considered cross-sectional data and would not be analyzed as a time series. ⊚ ⊚

true false

76) Mathematical models can be used to fit trends in time series but their predictive value is not guaranteed. ⊚ ⊚

true false

77) Analysts are usually successful at isolatingrandom noise within a time series and forecasting based on this. ⊚ ⊚

true false

78) A firm’s balance sheet contains data measured over a period of time, as opposed to being measured at a point in time. ⊚ ⊚

true false

79) Additive models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time. Version 1

⊚ ⊚

true false

80) Multiplicative models are most appropriate over longer periods of time or when the data magnitude is growing rapidly over time. ⊚ ⊚

81)

Multiplicative models are avoided in business because they are too complicated. ⊚ ⊚

82)

true false

Seasonality is usually ignored because there is no statistical way to describe it. ⊚ ⊚

84)

true false

Cycles are usually ignored because there is no general theory to describe them. ⊚ ⊚

83)

true false

Moving average models are causal models (as opposed to time-series models). ⊚ ⊚

Version 1

true false

85) Exponential smoothing and moving averages are especially useful for data with a clear trend. ⊚ ⊚

86)

Exponential smoothing is the same thing as fitting an exponential model to a time series. ⊚ ⊚

87)

true false

Over the short run, exponential and linear trends may look alike. ⊚ ⊚

90)

true false

An exponential trend allows growth but cannot be used if the time series is declining. ⊚ ⊚

89)

true false

An exponential trend can have a turning point (peak or trough). ⊚ ⊚

88)

true false

The quadratic model can never have more than one turning point (peaks or troughs). ⊚ ⊚

Version 1

true false

91) data.

The quadratic model’s R2 is always at least as high as the linear model fitted to the same

⊚ ⊚

92)

true false

The linear model’s R2 may exceed the quadratic model’s R2 fitted to the same data. ⊚ ⊚

true false

The shape of the fitted quadratic model yt = 544 + 62 t − 3.2 t2 first is declining at first, 93) then rising. ⊚ ⊚

true false

The shape of the fitted quadratic model yt = 324 − 42 t − 1.3 t is declining at first, then 94) rising. ⊚ ⊚

true false

The shape of the fitted quadratic model yt = 823 + 72 t − 5.1 t is rising at first, then 95) declining. ⊚ ⊚

Version 1

true false

96)

The shape of the fitted exponential model yt = 256 e−.07t is always declining. ⊚ ⊚

97)

The shape of the fitted exponential model yt = 256 e−.07t is rising at first, then declining. ⊚ ⊚

98)

true false

Moving averages are often used for making long-term forecasts (e.g., five periods ahead). ⊚ ⊚

100)

true false

Moving averages are most useful for irregular data with no clear trend. ⊚ ⊚

99)

true false

The smoothing constant α indicates the weight assigned to the most recent forecast. ⊚ ⊚

true false

101) Increasing the smoothing constant α increases the weight assigned to the most recent observation. ⊚ ⊚

Version 1

true false

102) data.

A higher value of the smoothing constant α makes the forecast less responsive to recent

⊚ ⊚

true false

103) Using the first observed data value is a common way of initializing the forecasts in the exponential smoothing model. ⊚ ⊚

104)

In exponential smoothing, using α = .20 will give a smoother series than using α = .05. ⊚ ⊚

105)

true false

Monthly seasonal factors should be adjusted so they sum to 12. ⊚ ⊚

107)

true false

In exponential smoothing, using α = .20 will provide less smoothing than using α = .10. ⊚ ⊚

106)

true false

Quarterly seasonal factors will sum to 4.00.

Version 1

⊚ ⊚

108)

Occam’s Razor says we should always choose the simplest model. ⊚ ⊚

109)

true false

An attraction of MAPE as a measure of fit is its simple interpretation. ⊚ ⊚

110)

true false

The MAD measures the average absolute size of the forecast error. ⊚ ⊚

true false

111) A centered moving average provides good forecasts when there is a strong upward trend in the data. ⊚ ⊚

true false

112) Over long periods of time, multiplicative time-series models may be favored over additive time-series models, because the data magnitude often changes over time. ⊚ ⊚

Version 1

true false

113) Regression analysis can be used for forecasting monthly time-series data using a trend variable and 11 binary predictors (one for each month except omitting one month). ⊚ ⊚

true false

114) The shape of the fitted quadratic model yt = 248 − 84 t + 2.4 t is declining at first, then rising. ⊚ ⊚

true false

115) Averaging the first six data values is a way of initializing the forecasts in an exponential smoothing process. ⊚ ⊚

true false

116) The exponential model would be attractive for analyzing a growing company’s revenues over time. ⊚ ⊚

117)

true false

If Y1 = 216 and Y5 = 332, then the simple index number for period 5 is I5 = 153.7. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 14_7e_Doane 1) B 2) C 3) A 4) B 5) D 6) B 7) A 8) A 9) C 10) D 11) A 12) D 13) C 14) D 15) D 16) B 17) A 18) B 19) A 20) A 21) A 22) D 23) D 24) D 25) B 26) D Version 1

27) A 28) C 29) C 30) B 31) C 32) B 33) A 34) D 35) A 36) B 37) D 38) A 39) C 40) B 41) B 42) D 43) B 44) D 45) B 46) D 47) D 48) C 49) B 50) D 51) B 52) C 53) B 54) B 55) C 56) A Version 1

57) A 58) B 59) C 60) A 61) D 62) A 63) C 64) B 65) D 66) A 67) B 68) C 69) A 70) C 71) B 72) C 73) TRUE 74) TRUE 75) FALSE 76) TRUE 77) FALSE 78) FALSE 79) FALSE 80) TRUE 81) FALSE 82) TRUE 83) FALSE 84) FALSE 85) FALSE 86) FALSE Version 1

87) FALSE 88) FALSE 89) TRUE 90) TRUE 91) TRUE 92) FALSE 93) FALSE 94) FALSE 95) TRUE 96) TRUE 97) FALSE 98) TRUE 99) FALSE 100) FALSE 101) TRUE 102) FALSE 103) TRUE 104) FALSE 105) TRUE 106) TRUE 107) TRUE 108) FALSE 109) TRUE 110) TRUE 111) FALSE 112) TRUE 113) TRUE 114) TRUE 115) TRUE 116) TRUE Version 1

117) TRUE

Version 1

CHAPTER 15 1) If samples are drawn from a population that is normal, a goodness-of-fit test for normality could yield

A) Type I error but not Type II error. B) Type II error but not Type I error. C) either Type I error or Type II error. D) both Type I and Type II errors.

2) The number of cars waiting at a certain residential neighborhood stoplight is observed at 6:00 a.m. on 160 different days. The observed sample frequencies are shown here. Number of cars waiting Number of days

0 60

1 50

2 30

3 20

Under the null hypothesis of a uniform distribution, the expected number of days we would see 0 cars is A) 10. B) 20. C) 30. D) 40.

3) A chi-square goodness of fit test for a normal distribution used 40 observations, and the mean and standard deviation were estimated from the sample. The test used six categories. We would use how many degrees of freedom in looking up the critical value for the test?

A) 39 B) 37 C) 5 D) 3

Version 1

4) A chi-square goodness of fit test for a normal distribution used 60 observations, and the mean and standard deviation were estimated from the sample. The test used seven categories. We would use how many degrees of freedom in looking up the critical value for the test?

A) 6 B) 4 C) 59 D) 57

Which of these statements concerning a chi-square goodness-of-fit test is correct?

A) Data could be ratio or interval measurements. B) Population must be normally distributed. C) All the expected frequencies must be equal. D) Observed frequencies must be equal.

6) Which of the following is not a potential solution to the problem that arises when not all expected frequencies are 5 or more in a chi-square test for independence?

A) Combine some of the columns. B) Combine some of the rows. C) Increase the sample size. D) Add more rows or columns.

Which of these statements concerning a chi-square goodness-of-fit test is correct?

Version 1

A) It is inapplicable to test for a normal distribution with open-ended top and bottom classes. B) It is generally a better test than the chi-square test of independence. C) There is no way to get the degrees of freedom since the right tail goes to infinity. D) It can be used to test whether a sample follows a specified distribution.

8) A proofreader checked 160 ads for grammatical errors. The sample frequency distribution is shown below. Number of Errors Observed Frequency

0 10

1 65

2 71

3 14

Under the null hypothesis of a uniform distribution, the expected number of times we would get 0 errors is A) 10. B) 20. C) 30. D) 40.

9) A proofreader checked 160 ads for grammatical errors. The sample frequency distribution is shown below. Number of Errors Observed Frequency

0 10

1 65

2 71

3 14

A goodness-of-fit test to determine whether this sample came from a uniform distribution would result in a chi-square test statistic of approximately A) 55. B) 79. C) 85. D) 161.

Version 1

10) A proofreader checked 160 ads for grammatical errors. The distribution obtained is shown below. Number of Errors Observed Frequency

0 10

1 65

2 71

3 14

At α = .01, what decision would we reach in a goodness-of-fit test to see whether this sample came from a uniform distribution? A) Reject the null and conclude the distribution is not uniform. B) Conclude that there is insufficient evidence to reject the null. C) No conclusion can be made due to small expected frequencies. D) No conclusion can be made due to inadequate sample size.

11)

A chi-square test of independence is a one-tailed test. The reason is that

A) we are testing whether the frequencies exceed their expected values. B) we square the deviations, so the test statistic lies at or above zero. C) hypothesis tests are one-tailed tests when dealing with sample data. D) the chi-square distribution is positively skewed.

12)

We sometimes combine two row or column categories in a chi-square test when the

A) observed frequencies are more than 5. B) observed frequencies are less than 5. C) expected frequencies are more than 5. D) expected frequencies are less than 5.

Version 1

13) To determine how well an observed set of frequencies fits an expected set of frequencies from a Poisson distribution we must estimate

A) no parameters. B) one parameter ( λ). C) two parameters ( μ, σ). D) three parameters ( μ, σ, n).

14)

The critical value in a chi-square test for independence depends on

A) the normality of the data. B) the variance of the data. C) the number of categories. D) the expected frequencies.

15)

In a chi-square test of independence, the number of degrees of freedom equals the

A) number of observations minus one. B) number of categories minus one. C) number of rows minus one times the number of columns minus one. D) number of sample observations minus the missing observations.

16)

In order to apply the chi-square test of independence, we must have

A) at least five observed frequencies in each cell. B) at least five expected observations in each cell. C) at least 5 percent of the observations in each cell. D) not more than five observations in each cell.

Version 1

17) Kortholts that fail to meet certain precise specifications must be reworked on the next day until they are within the desired specifications. A sample of one day’s output of kortholts from the Melodic Kortholt Company showed the frequencies shown below.

Specification Met Specification Not Met Column Total

Plant A

Plant B

Row Total

185 15 200

85 15 100

270 30 300

Find the test statistic for a chi-square test of independence. A) 7.22 B) 4.17 C) 5.13 D) 6.08

18) Kortholts that fail to meet certain precise specifications must be reworked on the next day until they are within the desired specifications. A sample of one day’s output of kortholts from the Melodic Kortholt Company showed the frequencies shown below.

Specification Met Specification Not Met Column Total

Plant A

Plant B

Row Total

185 15 200

85 15 100

270 30 300

Find the p-value for the chi-square test statistic for a hypothesis of independence. A) less than .01 B) between .01 and .025 C) between .025 and .05 D) greater than .05

Version 1

19) An operations analyst counted the number of arrivals per minute at a bank ATM in each of 30 randomly chosen minutes. The results were: 0, 3, 3, 2, 1, 0, 1, 0, 0, 1, 1, 1, 2, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 2, 0, 1, 0, 1. Which goodness-of-fit test would you recommend?

A) uniform B) poisson C) normal D) binomial

20) An operations analyst counted the number of arrivals per minute at an ATM in each of 30 randomly chosen minutes. The results were: 0, 3, 3, 2, 1, 0, 1, 0, 0, 1, 1, 1, 2, 1, 0, 1, 0, 1, 2, 1, 1, 2, 1, 0, 1, 2, 0, 1, 0, 1. For the Poisson goodness-of-fit test, what is the expected frequency of the data value X = 1?

A) impossible to determine B) 11.04 C) 1.00 D) 2.47

21) The table below is a tabulation of opinions of employees of Axolotl Corporation, who were sampled at random from pay records and asked to complete an anonymous job satisfaction survey.

Pay Type Salaried Hourly Column Total

Degree of Satisfaction Satisfied Neutral Dissatisfied 40 10 10 80 50 50 120 60 60

Row Total 60 180 240

For a chi-square test of independence, the degrees of freedom would be

Version 1

A) 2. B) 3. C) 4. D) 6.

22) The table below is a tabulation of opinions of employees of Axolotl Corporation, who were sampled at random from pay records and asked to complete an anonymous job satisfaction survey.

Pay Type Salaried Hourly Column Total

Degree of Satisfaction Satisfied Neutral Dissatisfied 40 10 10 80 50 50 120 60 60

Row Total 60 180 240

For a chi-square test of independence, what is the critical value for α = .01? A) 9.210 B) 4.605 C) 11.34 D) 16.81

23) The table below is a tabulation of opinions of employees of Axolotl Corporation, who were sampled at random from pay records and asked to complete an anonymous job satisfaction survey, with the results shown below.

Pay Type Salaried Hourly Column Total

Degree of Satisfaction Satisfied Neutral Dissatisfied 40 10 10 80 50 50 120 60 60

Row Total 60 180 240

Assuming independence, the expected frequency of satisfied hourly employees is

Version 1

A) 80. B) 90. C) 75. D) 60.

24)

To carry out a chi-square goodness-of-fit test for normality you need at least

A) five categories altogether. B) five observations in each category. C) five expected observations in each category. D) 50 samples or more.

25) Students in an introductory college economics class were asked how many credits they had earned in college and how certain they were about their choice of major. Their replies are summarized below.

Credits Earned Under 10 10 through 59 60 or more Column Total

Degree of Certainty Very Certain Very Certain Somewhat Certain 24 16 2 42

16 8 14 38

Row Total

6 20 22 48

46 44 38 128

Under the assumption of independence, the expected frequency in the upper left cell is A) 15.09. B) 24.00. C) 19.72. D) 20.22.

Version 1

26) Students in an introductory college economics class were asked how many credits they had earned in college and how certain they were about their choice of major. Their replies are summarized below.

Credits Earned Under 10 10 through 59 60 or more Column Total

Degree of Certainty Very Certain Very Certain Somewhat Certain 24 16 6 16 8 20 2 14 22 42 38 48

Row Total 46 44 38 128

For a chi-square test of independence, degrees of freedom would be A) 2. B) 9. C) 4. D) 127.

27) Students in an introductory college economics class were asked how many credits they had earned in college and how certain they were about their choice of major. Their replies are summarized below.

Credits Earned Under 10 10 through 59 60 or more Column Total

Degree of Certainty Very Certain Very Certain Somewhat Certain 24 16 6 16 8 20 2 14 22 42 38 48

Row Total 46 44 38 128

For a chi-square test of independence, which is the critical value for α = .05? A) 5.991 B) 7.815 C) 9.488 D) 16.92

Version 1

28) Students in an introductory college economics class were asked how many credits they had earned in college, and how certain they were about their choice of major. Their replies are summarized below.

Credits Earned Under 10 10 through 59 60 or more Column Total

Degree of Certainty Very Certain Very Certain Somewhat Certain 24 16 6 16 8 20 2 14 22 42 38 48

Row Total 46 44 38 128

Assuming independence, which is the expected frequency of very uncertain students with 60 credits or more? A) 12.47 B) 2.00 C) 14.56 D) 11.09

29) Students in an introductory college economics class were asked how many credits they had earned in college, and how certain they were about their choice of major. Their replies are summarized below.

Credits Earned Under 10 10 through 59 60 or more Column Total

Degree of Certainty Very Certain Somewhat Very Certain Certain 24 16 6 16 8 20 2 14 22 42 38 48

Row Total 46 44 38 128

Which statement is most nearly correct?

Version 1

A) The contingency table violates Cochran’s Rule. B) Visual inspection of column frequencies suggests independence. C) At α = .05 we would easily reject the null hypothesis of independence. D) At α = .05 we cannot reject he null hypothesis of independence.

30) As an independent project, a team of statistics students tabulated the types of vehicles that were parked in four different suburban shopping malls.

Vehicle Type

Somerset

Car Minivan Full-size Van SUV Truck Column Total

44 21 2

Mall Location Oakland Great Lakes 49 36 15 18 3 3

19 14 100

27 6 100

Jamestown

Row Total

64 13 2

193 67 10

12 9 100

84 46 400

26 17 100

For a chi-square test of independence, the degrees of freedom would be A) 20. B) 12. C) 399. D) 6.

31) As an independent project, a team of statistics students tabulated the types of vehicles that were parked in four different suburban shopping malls.

Vehicle Type

Somerset

Car Minivan

44 21

Version 1

Mall Location Oakland Great Lakes 49 36 15 18

Jamestown

Row Total

64 13

193 67

Full-size Van SUV Truck Column Total

19 14 100

27 6 100

26 17 100

12 9 100

84 46 400

For a chi-square test of independence, the critical value for α = .10 is A) 10.64. B) 14.68. C) 28.41. D) 18.55.

32) As an independent project, a team of statistics students tabulated the types of vehicles that were parked in four different suburban shopping malls.

Vehicle Type

Somerset

Car Minivan Full-size Van SUV Truck Column Total

44 21 2

Mall Location Oakland Great Lakes 49 36 15 18 3 3

19 14 100

27 6 100

26 17 100

Jamestown

Row Total

64 13 2

193 67 10

12 9 100

84 46 400

Assuming independence, the expected frequency of SUVs in Jamestown is A) 12. B) 21. C) 75. D) 60.

Version 1

33) Employees of OxCo Manufacturing were surveyed to evaluate the company’s pension plan. The table below displays some of the results of the survey.

Years Employed Under 10 10 to 25 25 or more Column Total

Rating of Pension Plan Excellent Good Fair 26 37 17 80

92 159 69 320

92 133 55 280

Poor

Row Total

30 71 19 120

240 400 160 800

6.206 chi-square

The expected frequency for the shaded cell in row 2 and column 2 in the table would be A) 163. B) 158. C) 165. D) 160.

34) Employees of OxCo Manufacturing were surveyed to evaluate the company’s pension plan. The table below displays some of the results of the survey.

Years Employed Under 10 10 to 25 25 or more Column Total

Rating of Pension Plan Excellent Good Fair 26 37 17 80

92 159 69 320

92 133 55 280

Poor

Row Total

30 71 19 120

240 400 160 800

6.206 chi-square

Degrees of freedom for this test would be

Version 1

A) 6. B) 7. C) 799. D) 12.

35) Employees of OxCo Manufacturing were surveyed to evaluate the company’s pension plan. The table below displays some of the results of the survey.

Years Employed Under 10 10 to 25 25 or more Column Total

Rating of Pension Plan Excellent Good Fair 26 37 17 80

92 159 69 320

92 133 55 280

Poor

Row Total

30 71 19 120

240 400 160 800

6.206 chi-square

Which is the most appropriate conclusion? A) Do not reject H0. B) Reject H0 at α = .10. C) Reject H0 at α = .05. D) Reject H0 at α = .01.

36) You test a hypothesis of independence of two variables. The number of observations is 500 and you have classified the data into a 4 × 4 contingency table. The test statistic has degrees of freedom.

A) 16 B) 9 C) 499 D) 498

Version 1

You want to test the hypothesis that the prime rate and inflation are independent. The 37) following table is prepared for the test on the basis of the results of a random sample, collected in various countries and various time periods shown below.

Inflation Rates Under 5% 5% or more Column Total

Prime Rate 6-February 10-July 40 30 5 30 45 60

20-November 5 40 45

Row Total 75 75 150

Using α = .05, which is the critical value of the test statistic that you would use? A) 3.841 B) 12.59 C) 5.991 D) 7.815

38) You want to test the hypothesis that the prime rate and inflation are independent. The following table is prepared for the test on the basis of the results of a random sample, collected in various countries and various time periods shown below.

Inflation Rates Under 5% 5% or more Column Total

6-February 40 5 45

Prime Rate 10-July 30 30 60

20-November 5 40 45

Row Total 75 75 150

The expected frequency for the cell in row 2 and column 3 is A) 22.5. B) 30. C) 40. D) 40.5.

Version 1

You want to test the hypothesis that the prime rate and inflation are independent. The 39) following table is prepared for the test on the basis of the results of a random sample, collected in various countries and various time periods shown below.

Inflation Rates Under 5% 5% or more Column Total

Prime Rate 6-February 10-July 40 30 5 30 45 60

20-November 5 40 45

Row Total 75 75 150

What is the value of the test statistic? A) 306.25 B) 0.00 C) 54.44 D) 13.61

40) You want to test the hypothesis that the prime rate and inflation are independent. The following table of frequencies is prepared from a random sample, collected in various countries and various time periods shown below.

Inflation Rates Under 5% 5% or more Column Total

Prime Rate 6-February 10-July 40 30 5 30 45 60

20-November 5 40 45

Row Total 75 75 150

Based on an analysis of the data in this table, which conclusion can be made at α = .01? A) The prime rate and inflation rate are independent. B) The prime rate and inflation rate are not independent. C) Small observed frequencies in some cells suggest that no reliable conclusion can be made. D) Small expected frequencies in some cells suggest that no reliable conclusion can be made.

Version 1

You want to sell your house, and you decide to obtain an appraisal on it. Looking at past 41) data, you discover that actual prices obtained for houses and the appraisals given for them prior to their sale were as shown below.

Appraisal Up to $500,000 $500,001 or more Column Total

Actual Selling Price Up to $500,001 or more $500,000 21 9 14 6 35 15

Row Total 30 20 50

Based on these data we can say that A) no conclusion is possible without knowing α. B) appraisal and actual price are not independent at α = .05. C) appraisal and actual price are independent at any α. D) the degrees of freedom are insufficient for a decision.

42) Preferences for the type of diet drink from a random sample of 121 shoppers are in the table below. A researcher is interested in determining if there is a relationship between the type of diet drink preferred and the age of the shoppers.

Diet Pepsi

Diet Coke

Version 1

Under 25

25 and older

Total

Observed Expected

10 21.40

60 48.60

70 70.00

% of chisq

28.6%

12.6%

41.3%

Observed Expected

18 9.79

14 22.21

32 32.00

% of chisq

32.5%

14.3%

46.8%

Diet Sprite

Total

Observed Expected

9 5.81

10 13.19

19 19.00

% of chisq

8.3%

3.6%

11.9%

Observed Expected

37 37.00

84 84.00

121 121.00

% of chisq

69.4%

30.6%

100.0%

21.21 chi-square

In performing a chi-square test of independence on these data, how many degrees of freedom will the test statistic have? A) 1 B) 2 C) 4 D) 6

43) Preferences for the type of diet drink from a random sample of 121 shoppers are in the table below. A researcher is interested in determining if there is a relationship between the type of diet drink preferred and the age of the shoppers.

Diet Pepsi

Diet Coke

Version 1

Under 25

25 and older

Total

Observed Expected

10 21.40

60 48.60

70 70.00

% of chisq

28.6%

12.6%

41.3%

Observed Expected

18 9.79

14 22.21

32 32.00

% of chisq

32.5%

14.3%

46.8%

Diet Sprite

Total

Observed Expected

9 5.81

10 13.19

19 19.00

% of chisq

8.3%

3.6%

11.9%

Observed Expected

37 37.00

84 84.00

121 121.00

% of chisq

69.4%

30.6%

100.0%

21.21 chi-square

Using α = .025, what is the critical value of the test statistic that you would use in a decision rule to test an appropriate hypothesis? A) 5.02 B) 5.99 C) 7.38 D) 14.45

44) Preferences for the type of diet drink from a random sample of 121 shoppers are in the table below. A researcher is interested in determining if there is a relationship between the type of diet drink preferred and the age of the shoppers.

Diet Pepsi

Diet Coke

Version 1

Under 25

25 and older

Total

Observed Expected

10 21.40

60 48.60

70 70.00

% of chisq

28.6%

12.6%

41.3%

Observed Expected

18 9.79

14 22.21

32 32.00

Diet Sprite

Total

% of chisq

32.5%

14.3%

46.8%

Observed Expected

9 5.81

10 13.19

19 19.00

% of chisq

8.3%

3.6%

11.9%

Observed Expected

37 37.00

84 84.00

121 121.00

% of chisq

69.4%

30.6%

100.0%

21.21 chi-square

What can you conclude for the data analysis at α = .05? A) The means are equal for all three groups. B) There is insufficient evidence to conclude that the type of drink and age are dependent. C) The type of drink and age are dependent. D) No conclusion is possible without knowing more information.

45) A taste test of randomly selected students was conducted to see if there was a difference in preferences among four popular drinks. The following table shows the frequency of responses. Beverage Frequency

Coke 51

Pepsi 66

A&W Root Beer 43

Dr Pepper 40

The expected number of students preferring Dr. Pepper is A) 25 B) 40 C) 50 D) 60

Version 1

46) A taste test of randomly selected students was conducted to see if there was a difference in preferences among four popular drinks. The following table shows the frequency of responses. Beverage Frequency

Coke 51

Pepsi 66

A&W Root Beer 43

Dr Pepper 40

Using α = .025, the critical value of the test you would use in determining whether the preferences are the same among the drinks is A) 5.991. B) 7.378. C) 9.348. D) 11.07.

47) U.S. market share for smartphones with larger screens is increasing. The national proportions for ownership by screen size are shown in the table below. Does smartphone ownership by college students follow the national trend? A chi-square goodness of fit test was performed. Smartphone Screen Size

4 inches or more 3.5 to 3.9 inches less than 3.5 inches

National Proportions Observed Frequency (n = 148 college students) 0.24 30 0.4 75 0.36 43

State the null and alternative hypotheses for this goodness-of-fit test.

Version 1

A) H0: Smartphone ownership by age follows the national proportions.H1: Smartphone ownership by age does not follow the national proportions. B) H0: Smartphone ownership by age does not follow the national proportions.H1: Smartphone ownership by age follows the national proportions. C) H0: Smartphone ownership by age is uniformly distributed.H1: Smartphone ownership by age is not uniformly distributed. D) H0: Smartphone ownership by age is not uniformly distributed.H1: Smartphone ownership by age is uniformly distributed.

48) U.S. market share for smartphones with larger screens is increasing. The national proportions for ownership by screen size are shown in the table below. Does smartphone ownership by college students follow the national trend? A chi-square goodness of fit test was performed and the p-value = .0293. The correct conclusion for an α = .05 would be Smartphone Screen Size

4 inches or more 3.5 to 3.9 inches less than 3.5 inches

National Proportions Observed Frequency (n = 148 college students) 0.24 30 0.4 75 0.36 43

A) smartphone ownership by age follows a uniform distribution. B) smartphone ownership by age does not follow the national proportions. C) smartphone ownership by age follows the national proportions. D) smartphone ownership by age is not uniformly distributed.

49) A taste test of randomly selected students was conducted to see if there was a difference in preferences among four popular drinks. The following table shows the frequency of responses. Beverage Frequency

Coke 51

Pepsi 66

A&W Root Beer 43

Dr Pepper 40

The value of the chi-square test statistic you would use in testing whether the preferences are the same among the drinks is

Version 1

A) 7.54. B) 8.12. C) 10.76. D) 12.56.

50) A taste test of randomly selected students was conducted to see if there was a difference in preferences among four popular drinks. The following table shows the frequency of responses. Beverage Frequency

Coke 51

Pepsi 66

A&W Root Beer 43

Dr Pepper 40

Using α = .025, what can you conclude from your analysis? A) Reject the null and conclude some drinks are preferred more than others. B) There is not enough evidence to say that a preference exists. C) Pepsi is the preferred drink. D) Form no conclusion because Cochran’s Rule is violated.

51) The Oxnard Retailers Anti-Theft Alliance (ORATA) published a study that claimed the causes of disappearance of inventory in retail stores were 30 percent shoplifting, 50 percent employee theft, and 20 percent faulty paperwork. The manager of the Melodic Kortholt Outlet performed an audit of the disappearance of 80 items and found the frequencies shown below. She would like to know if her store’s experience follows the same pattern as other retailers. Reason Frequency

Shoplifting 32

Employee Theft 38

Poor Paperwork 10

Under the null hypothesis that her store follows the published pattern, the expected number of items that disappeared due to shoplifting is

Version 1

A) 16. B) 40. C) 24. D) 27.

52) The Oxnard Retailers Anti-Theft Alliance (ORATA) published a study that claimed the causes of disappearance of inventory in retail stores were 30 percent shoplifting, 50 percent employee theft, and 20 percent faulty paperwork. The manager of the Melodic Kortholt Outlet performed an audit of the disappearance of 80 items and found the frequencies shown below. She would like to know if her store’s experience follows the same pattern as other retailers. Reason Frequency

Shoplifting 32

Employee Theft 38

Poor Paperwork 10

Using α = .05, the critical value you would use in determining whether the Melodic Kortholt Outlet’s pattern differs from the published study is A) 7.815. B) 5.991. C) 1.960. D) 1.645.

53) The Oxnard Retailers Anti-Theft Alliance (ORATA) published a study that claimed the causes of disappearance of inventory in retail stores were 30 percent shoplifting, 50 percent employee theft, and 20 percent faulty paperwork. The manager of the Melodic Kortholt Outlet performed an audit of the disappearance of 80 items and found the frequencies shown below. She would like to know if her store’s experience follows the same pattern as other retailers. Reason Frequency

Shoplifting 32

Employee Theft 38

Poor Paperwork 10

The value of the chi-square test statistic you would use in testing whether there is a difference from the published pattern is

Version 1

A) 7.54. B) 5.02 C) 9.76. D) 9.22.

54) The Oxnard Retailers Anti-Theft Alliance (ORATA) published a study that claimed the causes of disappearance of inventory in retail stores were 30 percent shoplifting, 50 percent employee theft, and 20 percent faulty paperwork. The manager of the Melodic Kortholt Outlet performed an audit of the disappearance of 80 items and found the frequencies shown below. She would like to know if her store’s experience follows the same pattern as other retailers. Reason Frequency

Shoplifting 32

Employee Theft 38

Poor Paperwork 10

Using α = .05, what can you conclude from your analysis? A) The store’s pattern is clearly significantly different from the published data. B) The store’s pattern is almost, but not quite, significantly different from the published data. C) The store’s pattern is very close to the published data. D) We can form no conclusion because Cochran’s Rule is violated.

55)

A contingency table shows

A) frequency counts. B) means of the data. C) event probabilities. D) chi-square values.

56)

We would create a contingency table by

Version 1

A) summing the probabilities of two variables. B) cross-tabulating frequencies of two variables. C) applying the chi-square distribution to a sample. D) using Cochran’s Rule to estimate frequencies.

57)

Which data set is consistent with the hypothesis of a normal population?

A) Data Set A B) Data Set C C) Neither data set. D) Both data sets.

58)

Which statement is most nearly correct regarding ECDF tests?

A) An attraction of the Anderson-Darling test is that it is fairly easy to do without a computer. B) In an ECDF test for goodness-of-fit, the n observations are grouped into categories rather than being treated individually. C) When raw data are available, ECDF tests usually surpass the chi-square test in their ability to detect departures from the distribution specified in the null hypothesis.

Version 1

59) Sam wants to perform a goodness-of-fit test for a Poisson distribution using the following sample data on the frequency of arrivals per minute. What value should Sam use to estimate the required parameter ( λ)? x 0 1 2 3 4 5 6 Total

f 3 9 14 11 7 4 2 50

A) 1.9 B) 2.1 C) 2.6 D) 3.1

60)

In a chi-square test of a 5 × 5 contingency table at α = .05, the critical value is 37.65. ⊚ ⊚

61) zero.

true false

If two variables are independent, we would anticipate a chi-square test statistic close to

⊚ ⊚

true false

62) The null hypothesis for a chi-square test on a contingency table is that the variables are dependent. ⊚ ⊚ Version 1

true false 28

63) The alternative hypothesis for a chi-square test on a contingency table is that the variables are dependent. ⊚ ⊚

64)

The shape of the chi-square distribution depends only on its degrees of freedom. ⊚ ⊚

65)

true false

The shape of the chi-square distribution is always skewed to the right. ⊚ ⊚

true false

66) In a chi-square test for independence, expected frequencies must be integers (or rounded to the nearest integer). ⊚ ⊚

67) cell.

true false

In a chi-square test for independence, observed frequencies must be at least 5 in every

⊚ ⊚

Version 1

true false

68) In a chi-square test for independence, observed and expected frequencies must sum across to the same row totals and down to the same column totals. ⊚ ⊚

69)

true false

The mean of the chi-square distribution is its degrees of freedom. ⊚ ⊚

true false

70) In samples drawn from a population in which the row and column categories are independent, the value of the chi-square test statistic will be zero. ⊚ ⊚

true false

71) In a hypothesis test using chi-square, if the null hypothesis is true, the sample value of the sample chi-square test statistic will be exactly zero. ⊚ ⊚

true false

72) The chi-square test for independence is a nonparametric test (no parameters are estimated). ⊚ ⊚

true false

73) Cochran’s Rule requires observed frequencies of 5 or more in each cell of a contingency table.

Version 1

⊚ ⊚

true false

74) A large negative chi-square test statistic would indicate that the null hypothesis should be rejected. ⊚ ⊚

75)

true false

The degrees of freedom in a 3 × 4 chi-square contingency table would equal 11. ⊚ ⊚

true false

76) The null hypothesis for a chi-square contingency test of independence for two variables always assumes that the variables are independent. ⊚ ⊚

true false

77) The chi-square test is unreliable when there are any cells with small observed frequency counts. ⊚ ⊚

78)

true false

The chi-square test can only be used to assess independence between two variables. ⊚ ⊚

Version 1

true false

79)

The chi-square test is based on an analysis of frequencies. ⊚ ⊚

80)

true false

A chi-square distribution is always skewed right. ⊚ ⊚

true false

81) A chi-square test for independence is called a distribution-free test because the test is based on categorical data rather than on populations that follow any particular distribution. ⊚ ⊚

true false

82) Observed frequencies in a chi-square goodness-of-fit test for normality may be less than 5, or even 0, in some cells, as long as the expected frequencies are large enough. ⊚ ⊚

true false

83) In a chi-square goodness-of-fit test, a small p-value would indicate a good fit to the hypothesized distribution. ⊚ ⊚

Version 1

true false

84) For a chi-square goodness-of-fit test for a uniform distribution with 5 categories, we would use the critical value for 4 degrees of freedom. ⊚ ⊚

true false

85) For a chi-square goodness-of-fit test for a uniform distribution with 7 categories, we would use the critical value for 6 degrees of freedom. ⊚ ⊚

true false

86) For a chi-square goodness-of-fit test for a normal distribution using 8 categories with estimated mean and standard deviation, we would use the critical value for 7 degrees of freedom. ⊚ ⊚

true false

87) For a chi-square goodness-of-fit test for a normal distribution using 7 categories with estimated mean and standard deviation, we would use the critical value for 4 degrees of freedom. ⊚ ⊚

88)

true false

A probability plot usually allows outliers to be detected. ⊚ ⊚

true false

89) In a goodness-of-fit test, a linear probability plot suggests that the null hypothesis should be rejected.

Version 1

⊚ ⊚

true false

90) In a chi-square goodness-of-fit test, we lose one degree of freedom for each parameter estimated. ⊚ ⊚

91)

true false

In a chi-square goodness-of-fit test, we gain one degree of freedom if n increases by 1. ⊚ ⊚

true false

92) In a chi-square goodness-of-fit test, a sample of n observations has n − 1 degrees of freedom. ⊚ ⊚

93)

true false

The Poisson goodness-of-fit test is inappropriate for continuous data. ⊚ ⊚

true false

94) The Kolmogorov-Smirnov and Anderson-Darling tests are based on the ECDF (Empirical Cumulative Distribution Function). ⊚ ⊚

Version 1

true false

95) Goodness-of-fit tests using the ECDF (Empirical Cumulative Distribution Function) compare the actual cumulative frequencies with expected cumulative frequencies for each observation under the assumption that the data came from the hypothesized distribution. ⊚ ⊚

true false

96) An attraction of the Kolmogorov-Smirnov test is that it is fairly easy to do without a computer. ⊚ ⊚

true false

97) An attraction of the Anderson-Darling test is that it is fairly easy to do without a computer. ⊚ ⊚

true false

98) ECDF tests have an advantage over the chi-square goodness-of-fit test on frequencies because an ECDF test treats observations individually. ⊚ ⊚

99)

true false

The chi-square test lacks power when the sample size is small. ⊚ ⊚

Version 1

true false

100) In an ECDF test for goodness-of-fit, the n observations are grouped into categories rather than being treated individually. ⊚ ⊚

true false

101) When raw data are available, ECDF tests usually surpass the chi-square test in their ability to detect departures from the distribution specified in the null hypothesis. ⊚ ⊚

102)

The Anderson-Darling test is used to test the assumption of normality. ⊚ ⊚

103)

true false

Probability plots are used to test the assumption of normality. ⊚ ⊚

true false

104) In a test for a uniform distribution with k categories, the expected frequency is n/ k in each cell. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 15_7e_Doane 1) A 2) D 3) D 4) B 5) A 6) D 7) D 8) D 9) B 10) A 11) B 12) D 13) B 14) C 15) C 16) B 17) B 18) C 19) B 20) B 21) A 22) A 23) B 24) C 25) A 26) C Version 1

27) C 28) A 29) C 30) B 31) D 32) B 33) D 34) A 35) A 36) B 37) C 38) A 39) C 40) B 41) C 42) B 43) C 44) C 45) C 46) C 47) A 48) B 49) B 50) B 51) C 52) B 53) B 54) B 55) A 56) B Version 1

57) A 58) C 59) C 60) FALSE 61) TRUE 62) FALSE 63) TRUE 64) TRUE 65) TRUE 66) FALSE 67) FALSE 68) TRUE 69) TRUE 70) FALSE 71) FALSE 72) TRUE 73) FALSE 74) FALSE 75) FALSE 76) TRUE 77) FALSE 78) FALSE 79) TRUE 80) TRUE 81) TRUE 82) TRUE 83) FALSE 84) TRUE 85) TRUE 86) FALSE Version 1

87) TRUE 88) TRUE 89) FALSE 90) TRUE 91) FALSE 92) FALSE 93) TRUE 94) TRUE 95) TRUE 96) FALSE 97) FALSE 98) TRUE 99) TRUE 100) FALSE 101) TRUE 102) TRUE 103) TRUE 104) TRUE

Version 1

CHAPTER 16 1)

All of these are nonparametric tests except

A) Spearman rank correlation test. B) Friedman test. C) Student’s t test. D) Kruskal-Wallis test.

Which nonparametric test is analogous to a parametric two-sample t test for means?

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

Which nonparametric test is analogous to a parametric k-sample test for means?

A) Kruskal-Wallis test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Wald-Wolfowitz one-sample runs test

Which nonparametric test is used to compare a one-sample median with a benchmark?

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

Version 1

Which nonparametric test has no parametric counterpart?

A) Wald-Wolfowitz one-sample runs test B) Spearman rank correlation test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

6) Which nonparametric test is analogous to a parametric one-sample t test for differences in paired data?

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

7) Which nonparametric test would we use to compare ratings assigned to n pairs of bonds by two different rating agencies if the bonds are rated on an ordinal scale (Aaa, Aa, A, Baa, Ba B, etc.)?

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

Which is not true of the one-sample runs test?

Version 1

A) It is also called the Wald-Wolfowitz test after its inventors. B) Its purpose is to detect nonrandomness. C) It cannot be applied to sequential observations. D) It is similar to a test for autocorrelation.

Which nonparametric test is used to detect nonrandomness in sequential observations?

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

10)

Which is a nonparametric test for runs (autocorrelation) in a sequence of binary data?

A) Kruskal-Wallis test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Wald-Wolfowitz one-sample runs test

11)

Which parametric test resembles the nonparametric Spearman’s rank test?

A) t test of a correlation coefficient B) t test of two sample means C) t test of one sample mean D) F test of variances

12)

Which nonparametric test is used to test for agreement in ranks of paired data?

Version 1

A) Spearman test B) Friedman test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

13) Twenty customers are randomly chosen, and each is given a sample of Nut Butter ice cream to taste. The customers rank the taste of the ice cream on a 10-point scale. Each is then given a sample of Chewy Gooey ice cream to taste and rank on a 10-point scale. Based on the 20 customers’ ratings of each flavor, the research analyst conducting the survey wishes to determine if one flavor is preferred over the other. Which nonparametric test would you use to determine if there is a difference in the ratings?

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

14)

Which is not a characteristic of the Wilcoxon rank sum (Mann-Whitney) test?

A) It can be used as a test for equality of two population medians. B) It is analogous to a one-sample t test comparing a mean with a benchmark. C) It requires independent samples from populations with equal variances. D) It is similar to one-factor ANOVA when we have c independent samples.

15) Delta Air Lines wants to determine if the number of no-shows for flights originating from Detroit is higher than from Minneapolis. A sample of 20 flights is taken from each city, and the number of no-shows is determined for each flight. Which nonparametric test would you use to determine whether the number of no-shows is greater in Detroit?

Version 1

A) Wald-Wolfowitz one-sample runs test B) Wilcoxon signed-rank test C) Wilcoxon rank sum (Mann-Whitney) test D) Kruskal-Wallis test

16) The dean of Oxnard business school wants to know if there is a difference in computer skills for students in four majors (marketing, finance, operations, accounting). A 20-question skills test is given to 10 randomly chosen students in each major. Which nonparametric test could be used by the dean to see if there is a difference in computer skills of students in the various majors?

A) Wald-Wolfowitz test B) Wilcoxon signed-rank test C) Mann-Whitney test D) Kruskal-Wallis test

17)

Which is not a characteristic of the Kruskal-Wallis test?

A) It is analogous to the parametric one-factor ANOVA. B) It does not make any assumptions about the populations. C) It is useful in comparing the medians in c groups. D) It does not require normal distributions of populations.

18) Individuals in four different age groups are asked to rate, on a scale of 1 to 10, three flavors of ice creams. Each group has the same number of individuals. Median ratings by the individuals are grouped by the flavor of ice cream and by age group. Which nonparametric test could be used to see if there is a difference in median ratings among the four age groups and three flavors?

Version 1

A) Wilcoxon signed-rank test B) Friedman test C) Mann-Whitney test D) Kruskal-Wallis test

19)

Which nonparametric test is analogous to a two-factor ANOVA without replication?

A) Wilcoxon signed-rank test B) Friedman test C) Mann-Whitney test D) Kruskal-Wallis test

20) If there are three or more populations with ordinal data, what is the appropriate test to determine whether the distributions are equal?

A) Friedman test B) t test C) ANOVA D) Kruskal-Wallis test

21) Hoping to reduce the waiting time, a doctor’s office tried a new way of scheduling its appointments. Populations of waiting times are believed to be similar except in central tendency. However, waiting times may not be normally distributed, so a nonparametric test was chosen to compare the waiting times. The Wilcoxon/Mann-Whitney test results are shown below.

Mann/Whitney Test sum of ranks

21 25

600.5 480.5

Version 1

Old Way New Way

1081

Total

expected value standard deviation z, corrected for ties p- value (one-tailed, upper)

493.50 45.31 2.35 .0094

Which is the best conclusion? A) The medians differ at α = .01. B) The means differ at α = .01. C) The samples differ at α = .01. D) There are no differences at α = .01.

22) At the Food Barn, children can order from the adult menu (A) or the child’s menu (C). Below is the pattern of menu orders for 24 children last Wednesday evening. A, A, A, A, C, A, A, C, C, C, A, A, A, A, A, A, C, C, C, A, C, C, C, C Which test would you choose to see if this pattern is random?

A) Kruskal-Wallis test B) Wilcoxon rank sum (Mann-Whitney) test C) Wald-Wolfowitz one-sample runs test D) Wilcoxon test

23) At the Food Barn, children can order from the adult menu (A) or the child’s menu (C). Below is the pattern of menu orders for 24 children last Wednesday evening. A, A, A, A, C, A, A, C, C, C, A, A, A, A, A, A, C, C, C, A, C, C, C, C Which statement is most accurate?

Version 1

A) Neither sample size (for outcomes A or C) is large enough for a runs test using z. B) Both sample sizes (for outcomes A and C) are large enough for a runs test using z. C) Only one outcome has a large enough sample for a runs test using z. D) This type of data would not be suitable for a runs test using z.

24) A clinic has four doctors. They wish to compare the amount of time that doctors spend with their patients. It is suspected that times may not be normally distributed but are otherwise assumed similar except in center, so a nonparametric test was chosen. The Kruskal-Wallis test results are shown below.

Median

Kruskal-Wallis Test Average Rank

27.00 28.50 46.00 31.00

11 14 9 11

19.18 15.93 36.39 24.86

31.00

Doctor A Doctor B Doctor C Doctor D Total

H (corrected for ties) d.f p-value

14.599 3 .0022

Which is the best conclusion? A) The doctors have the same median times at α = .01. B) The doctors have different median times at α = .01. C) The sample size is insufficient for this kind of test. D) A one-factor ANOVA would be a better kind of test.

Version 1

25) Returns on an investor’s stock portfolio ( n = 19 stocks) are compared for the same stock in each of two consecutive quarters. Since the returns are not normally distributed (normality test p-values were .005 and .126 respectively), a nonparametric test was chosen. The test results are shown below.

Wilcoxon Paired Data Test sum of ranks

19 19

247 494

Quarter 1 Quarter 2

741

total

expected value standard deviation z p- value (two-tailed)

370.50 34.25 −3.59 .0003

Which is the best conclusion? A) The means are the same at α = .01. B) The medians are the same at α = .01. C) The means differ at α = .01. D) The medians differ at α = .01.

26) Returns on an investor’s stock portfolio ( n = 19 stocks) are compared for the same stock in each of two consecutive quarters. Since the returns are not normally distributed (normality test p-values were .005 and .126 respectively), a nonparametric test was chosen. The test results are shown below. Spearman Rank Correlation Quarter 1 Quarter 1 1.000 Quarter 2 .577 sample size critical value .05 (two-tail) critical value 0.15 (two-tail)

Quarter 2 .577 1.000 19 ±.456 ±.575

Which is the best conclusion? Version 1

A) The returns are correlated neither at α = .05 nor at α = .01. B) The returns are correlated at α = .05 but not at α = .01. C) The returns are correlated at α = .01 but not at α = .05. D) The returns are correlated both at α = .05 and at α = .01.

27) Attendees at an outdoor concert can buy pavilion tickets (A) or lawn tickets (B). Below is the output for the one-sample runs to test whether there is a pattern in 32 consecutive ticket purchases. Runs Test runs

n 21 11

6 6

A B

total

expected value standard deviation z p- value (two-tailed)

15.44 2.50 −1.17 .2403

The best conclusion at α = .05 would be A) the pattern is random. B) there is a difference in medians. C) the sample sizes are too small. D) the sample sizes must be equal.

28) To compare the cost of three shipping methods, a firm shipped five orders to each of four different destinations over a six-month period. Their total shipping costs are shown below.

Destination Shipper

Version 1

Toledo

Oshawa

Janesville

Dallas

Speedy Ship GetItThere WeR Tops

355 342 361

435 441 430

422 402 435

518 488 528

Which nonparametric test would you use to compare the median shipping costs among destinations and among shippers? A) Friedman test B) Kruskal-Wallis test C) Wilcoxon rank sum (Mann-Whitney) test D) Lebesgue-Stieltjes test

29) At the Seymour Clinic, the total number of patients seen by three doctors over three days is shown.

Physician Day Monday Tuesday Wednesday Thursday Friday

Dr. Able 19 20 22 19 20

Dr. Baker 25 22 24 20 34

Dr. Chow 27 27 32 22 27

Which nonparametric test would you use to compare the median number of patients seen by the doctors on each day? A) Wilcoxon test B) Kruskal-Wallis test C) Anderson-Darling test D) Friedman test

Version 1

30) Systolic blood pressure of randomly selected HMO patients was recorded on a particular Wednesday, with the results shown below.

Under 20 105 113 108 114 123

Patient Age Group 20 to 29 30 to 49 110 122 101 114 112 128 127 124 123 125

50 and Over 139 115 136 124 123

Which is the appropriate hypothesis test to compare the medians? A) Wilcoxon test B) Kruskal-Wallis test C) Levene’s test D) Friedman test

31) You do not wish to assume normality in the population, yet you wish to compare central tendency in c samples. You decide to utilize MegaStat, whose menu is shown below.

Which menu would you choose? Version 1

A) Hypothesis Tests B) Nonparametric Tests C) Correlation/Regression D) Analysis of Variance

32) You do not wish to assume normality in the population, yet you wish to compare central tendency in c samples. You decide to utilize Minitab, whose menu is shown below.

Which menu would you choose? A) ANOVA B) Regression C) Nonparametrics D) EDA

33)

Nonparametric tests can be used with small samples. ⊚ ⊚

Version 1

true false

34)

Nonparametric tests may require special tables for small samples. ⊚ ⊚

true false

35) Nonparametric tests generally are more powerful than parametric tests when normality cannot be assumed. ⊚ ⊚

true false

36) Parametric tests generally are more powerful than nonparametric tests when normality can be assumed. ⊚ ⊚

true false

37) Rejection of a hypothesis using a nonparametric test is less convincing than using an equivalent parametric test, because nonparametric tests generally make fewer assumptions. ⊚ ⊚

true false

38) Rejection of a hypothesis using a nonparametric test is more convincing than using an equivalent parametric test when the data are badly skewed. ⊚ ⊚

Version 1

true false

39)

If the population is normal, we would usually prefer a nonparametric test. ⊚ ⊚

40)

Most nonparametric tests assume ordinal data. ⊚ ⊚

41)

true false

The one-sample runs test uses binary data (only two possible values). ⊚ ⊚

44)

true false

The one-sample runs test compares medians of two or more groups. ⊚ ⊚

43)

true false

Most nonparametric tests require data measured on a ratio scale. ⊚ ⊚

42)

true false

The Spearman rank correlation test compares medians of two paired data sets. ⊚ ⊚

Version 1

true false

45) The one-sample runs test uses a test statistic that is normally distributed as long as the number of runs of each type is large enough. ⊚ ⊚

46)

The one-sample runs test is useful for detecting nonrandom patterns in time-series data. ⊚ ⊚

47)

true false

The one-sample runs test is similar to a test for autocorrelation. ⊚ ⊚

48)

true false

The one-sample runs test is also called the Wald-Wolfowitz test after its inventors. ⊚ ⊚

true false

49) The Wilcoxon signed-rank test is useful when comparing one sample median with a benchmark. ⊚ ⊚

50)

true false

The Wilcoxon signed-rank test is useful when comparing more than two sample medians. ⊚ ⊚

Version 1

true false

51)

The Wilcoxon signed-rank test is analogous to a one-sample parametric test of a mean. ⊚ ⊚

true false

52) The Wilcoxon signed-rank test is analogous to a parametric two-sample t test of means from independent samples. ⊚ ⊚

true false

53) The Wilcoxon signed-rank test is analogous to a parametric t test comparing three or more medians. ⊚ ⊚

true false

54) The Wilcoxon signed-rank test is robust to outliers in the data if the population is at least somewhat symmetric. ⊚ ⊚

true false

55) The Wilcoxon signed-rank test does not assume a normal population, but it does require a roughly symmetric population. ⊚ ⊚

Version 1

true false

56) The Wilcoxon signed-rank test is less powerful than a one-sample test of a mean when the population is actually normal. ⊚ ⊚

57)

true false

The Wilcoxon signed-rank test has good power over a range of nonnormal populations. ⊚ ⊚

true false

58) The Wilcoxon signed-rank test is an alternative to the one-sample t test for paired observations. ⊚ ⊚

true false

59) The Wilcoxon rank sum test (Mann-Whitney test) can be used as a test for equality of two population medians. ⊚ ⊚

60)

true false

The Wilcoxon rank sum test (Mann-Whitney test) requires two independent samples. ⊚ ⊚

true false

61) The Wilcoxon rank sum test (Mann-Whitney test) can be used even when the population variances are unequal.

Version 1

⊚ ⊚

true false

62) The Wilcoxon rank sum test (Mann-Whitney test) utilizes the ranks of two independent samples. ⊚ ⊚

true false

63) The Mann-Whitney test is sometimes called the "Wilcoxon rank sum test" because it was formulated independently by different statisticians. ⊚ ⊚

true false

64) We sometimes call the Wilcoxon rank sum test the Mann/Whitney test, but the two are the same. ⊚ ⊚

true false

65) The Mann-Whitney test is analogous to a one-sample t test comparing a mean with a benchmark. ⊚ ⊚

66)

true false

The Kruskal-Wallis test requires c independent samples (where usually c > 2). ⊚ ⊚

Version 1

true false

67) The Kruskal-Wallis test applies even if the c samples to be compared are not independent. ⊚ ⊚

68)

The Kruskal-Wallis test is analogous to the one-sample parametric t test for a mean. ⊚ ⊚

69)

true false

The Kruskal-Wallis test is analogous to the parametric one-factor ANOVA. ⊚ ⊚

true false

70) The Kruskal-Wallis test does not require normal populations, but it does require them to be of similar shape. ⊚ ⊚

71)

The Kruskal-Wallis test is equivalent to comparing medians in c groups. ⊚ ⊚

72)

true false

The Kruskal-Wallis test is a test for randomness in sequential data.

Version 1

⊚ ⊚

true false

73) The Kruskal-Wallis test is less useful in finance or marketing, because normal populations can usually be assumed for financial or marketing data. ⊚ ⊚

true false

74) The Kruskal-Wallis test is almost as powerful as one-factor ANOVA even when normality can be assumed. ⊚ ⊚

true false

75) The Friedman test is a nonparametric equivalent to two-factor ANOVA without replication. ⊚ ⊚

true false

76) The Friedman test is a nonparametric equivalent to a parametric one-sample t test comparing a mean with a benchmark. ⊚ ⊚

77)

true false

The Friedman test requires groups of equal size. ⊚ ⊚

Version 1

true false

78) The Friedman test compares medians when there are two grouping factors (rows, columns). ⊚ ⊚

true false

79) The Friedman test resembles the Kruskal-Wallis test except that there are two grouping factors (rows, columns) instead of one grouping factor (columns). ⊚ ⊚

true false

80) The Friedman test is often almost as powerful as two-factor ANOVA without replication (randomized block design). ⊚ ⊚

81)

Spearman’s rank correlation always lies within the range −1.00 to +1.00. ⊚ ⊚

82)

true false

Spearman’s rank correlation coefficient lies within the range 0 to 1.00 inclusive. ⊚ ⊚

83)

true false

Spearman’s rank correlation is named for a British brewer who was testing beer samples.

Version 1

⊚ ⊚

true false

84) Spearman’s rank correlation is named for a British behavioral psychologist who was studying human intelligence. ⊚ ⊚

85) data.

true false

Spearman’s rank correlation is used to measure agreement in rankings of paired ( x, y)

⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 16_7e_Doane 1) C 2) C 3) A 4) B 5) A 6) B 7) B 8) C 9) A 10) D 11) A 12) A 13) B 14) D 15) C 16) D 17) B 18) B 19) B 20) D 21) A 22) C 23) B 24) B 25) D 26) D Version 1

27) A 28) A 29) D 30) B 31) B 32) C 33) TRUE 34) TRUE 35) TRUE 36) TRUE 37) FALSE 38) TRUE 39) FALSE 40) TRUE 41) FALSE 42) FALSE 43) TRUE 44) FALSE 45) TRUE 46) TRUE 47) TRUE 48) TRUE 49) TRUE 50) FALSE 51) TRUE 52) FALSE 53) FALSE 54) TRUE 55) TRUE 56) TRUE Version 1

57) TRUE 58) TRUE 59) TRUE 60) TRUE 61) FALSE 62) TRUE 63) TRUE 64) TRUE 65) FALSE 66) TRUE 67) FALSE 68) FALSE 69) TRUE 70) TRUE 71) TRUE 72) FALSE 73) FALSE 74) TRUE 75) TRUE 76) FALSE 77) TRUE 78) TRUE 79) TRUE 80) TRUE 81) TRUE 82) FALSE 83) FALSE 84) TRUE 85) TRUE

Version 1

CHAPTER 17 1)

Quality experts would probably not recommend

A) reducing variation. B) using control charts. C) placing blame for poor work. D) identifying sources of variation.

Quality is ultimately best assessed by

A) trained statisticians. B) quality control inspectors. C) management. D) customers.

Which is not a true statement about the life and philosophy of W. Edwards Deming?

A) He taught quality control techniques to Japanese companies during the 1950s. B) He lived a very long life and was a highly paid consultant past age 80. C) He invented control charts and proposed the ISO 9000 standard. D) He believed that poor quality is not primarily the fault of the workers.

Control charts (SPC charts) are attributed to

A) Deming. B) Shewhart. C) Juran. D) Taguchi.

Version 1

The development of acceptance sampling is attributed to the works of

A) Deming and Shewhart. B) Potter and Granger. C) Dodge and Romig. D) Taguchi and Ishikawa.

6) and are well known for their statistical work related to customer satisfaction and the cost of quality.

A) Deming; Shewhart B) Harold; Kumar C) Dodge; Romig D) Taguchi; Ishikawa

Which of the following is not a characteristic of Total Quality Management (TQM)?

A) employee empowerment B) reduction of waste C) continuous improvement D) reducing the Cp index

Which of the following is not a dimension of service quality?

Version 1

A) reliability B) taste C) empathy D) assurance

Which of the following is a map used to identify potential service failure points?

A) failure flows B) service failure chart C) failure blueprint D) service blueprint

10)

Instability is most readily apparent on the

A) chart. B) R chart. C) np chart. D) I chart.

11)

The problem that is probably the hardest to identify from a control chart is

A) mixture. B) oscillation. C) cycle. D) trend.

12)

Which is not a tool of statistical quality control?

Version 1

A) fishbone diagram B) pareto chart C) attribute control chart D) Deming chart

13)

Control charts were an innovation attributed to

A) Deming in the 1950s. B) Shewhart in the 1920s. C) Westinghouse in the 1960s. D) Pacioli in the 1490s.

14)

Which is an appropriate step in continuous quality improvement?

A) Taking measurements on a variable and keeping careful records. B) Posting quality banners or company flags where they are visible to all. C) Castigating the lazy employees for their shoddy workmanship. D) Sending employees to Motivation Camp taught by expensive consultants.

15)

Likely reasons for inaccurate control limits would include which of the following?

A) The engineering parameter for variance is unknown. B) The engineers were underpaid for their work. C) There was insufficient preliminary sampling. D) Process variation was not zero, as expected.

16)

Attribute control charts would not be used to display the

Version 1

A) proportion of nonconforming parts. B) sample range for a measured variable. C) total number of nonconforming parts. D) average number of nonconforming parts.

17)

The R chart is likely to reveal which problem?

A) instability B) cycles C) level shift D) trend

18)

Which of the following is most likely the cause of a level shift in a SPC chart?

A) tool wear B) a new worker C) temperature fluctuations D) alternating samples from two machines

19)

Instability in a process is indicated when samples

A) tend to alternate between high and low values. B) drift slowly either upward or downward. C) vary more than expected. D) shift abruptly either above or below the centerline.

20)

A level shift in a process is indicated when samples

Version 1

A) tend to alternate between high and low values. B) drift slowly either upward or downward. C) vary more than expected. D) shift abruptly to a new mean.

21)

A slow drift of measurements either up or down from the process centerline suggests a(n)

A) mixed process. B) trend. C) instability. D) cycle.

22)

Which is not characteristic of a trend?

A) Variance is essentially unchanged from sample to sample. B) Trend is often due to mixing two batches of materials. C) Trend is detectable on a control chart if enough samples are taken. D) Rules of thumb can be established to detect trend.

23)

Which is not a rule of thumb to indicate an out-of-control process on the chart?

A) single point outside three sigma B) three of four successive points outside two sigma on the same side of the centerline C) four of five successive points outside one sigma on the same side of the centerline D) nine successive points on the same side of the centerline

24)

Which is not a characteristic of instability?

Version 1

A) larger than normal amount of variation B) higher-than-expected frequencies in tails of the distribution of means C) often caused by untrained operators D) specification limits that are too narrow

25)

Refer to the diagram below.

Which statement below is not supported by the diagram above? A) The Cpk < Cp. B) This process is not centered on target. C) The process is clearly capable of meeting the LSL. D) The process appears capable of meeting the USL.

26)

Find the Cp index for a process with USL = 550, LSL = 540, μ = 545, and σ = 0.75.

A) 1.25 B) 1.33 C) 2.22 D) 1.75

Version 1

27)

Find the Cpk index for a process with USL = 550, LSL = 540, μ = 545, and σ = 0.75.

A) 1.33 B) 2.22 C) 1.25 D) 1.75

28)

Find the Cp index for a process with USL = 550, LSL = 540, μ = 543, and σ = 0.75.

A) 1.25 B) 1.33 C) 2.22 D) 1.75

29)

Find the Cpk index for a process with USL = 550, LSL = 540, μ = 543, and σ = 0.75.

A) 1.33 B) 2.22 C) 1.25 D) 1.75

30)

Find the Cpk index for a process with USL = 550, LSL = 540, μ = 544, and σ = 1.25.

A) 1.33 B) 2.22 C) 1.07 D) 1.75

Version 1

31)

Is a process capable if USL = 550, LSL = 540, μ = 542, and σ = 1.25?

A) No, clearly not. B) No, but very close. C) Yes, just barely. D) Yes, highly capable.

32)

Statistical process control charts can measure

A) the stability of a process. B) the capability of a process to meet the LSL. C) the capability of a process to meet the USL. D) the validity of the LSL and USL.

33)

Process specification limits are determined by

A) the process behavior. B) the company’s management. C) the customer’s requirements. D) the process operators.

34)

In manufacturing, if workers readjust the equipment after each sample, it would typically

A) increase variation. B) decrease variation. C) widen the specification limits. D) improve conformance to specifications.

Version 1

35)

Which statistician developed the 14 Points of Quality?

A) Juran B) Deming C) Taguchi D) Ishikawa

36) If the specification subgroup size is n = 4 and the known process parameters are μ = 2.75 and σ = 0.044, which are the control limits for the chart?

A) LCL = 2.684, UCL = 2.816 B) LCL = 2.728, UCL = 2.772 C) LCL = 2.618, UCL = 2.882 D) LCL = 2.518, UCL = 2.998

37)

Which is not a characteristic of a p-chart?

A) It shows the number of defects per item being inspected. B) It measures the fraction of nonconforming items in a sample. C) It is based on the binomial distribution (or its normal approximation). D) It will have varying control limits if the sample size is changing.

Ten samples of n = 5 were collected to construct an chart. The sample mean and range 38) for each sample are shown in the table below. Sample 1 2 3

Version 1

Mean 215 204 160

Range 15 20 10 10

4 5 6 7 8 9 10

226 232 224 205 184 207 212

19 24 21 27 12 16 17

Calculate the empirical centerline for the chart. A) 210.5 B) 206.9 C) 205.3 D) 208.2

Ten samples of n = 5 were collected to construct an chart. The sample mean and range 39) for each sample are shown in the table below. Sample 1 2 3 4 5 6 7 8 9 10

Mean 215 204 160 226 232 224 205 184 207 212

Range 15 20 10 19 24 21 27 12 16 17

Calculate the empirical lower and upper control limits for the chart. (You will need a table of control chart factors.) Subgroup Size 2 3 4 5

Version 1

d2 1.128 1.693 2.059 2.326

D3 0 0 0 0

D4 3.267 2.574 2.282 2.114

6 7 8 9

2.534 2.704 2.847 2.970

0 0.076 0.136 0.184

2.004 1.924 1.864 1.816

A) LCL = 196.46, UCL = 217.34 B) LCL = 171.81, UCL = 241.39 C) LCL = 188.03, UCL = 225.17 D) LCL = 163.64, UCL = 250.56

Ten samples of n = 5 were collected to construct an chart. The sample mean and range 40) for each sample are shown in the table below. Sample 1 2 3 4 5 6 7 8 9 10

Mean 215 204 160 226 232 224 205 184 207 212

Range 15 20 10 19 24 21 27 12 16 17

Calculate the empirical centerline for the R chart. A) 20.8 B) 17.2 C) 18.1 D) 19.4

Ten samples of n = 5 were collected to construct an chart. The sample mean and range 41) for each sample are shown in the table below.

Version 1

Sample 1 2 3 4 5 6 7 8 9 10

Mean 215 204 160 226 232 224 205 184 207 212

Range 15 20 10 19 24 21 27 12 16 17

Calculate empirical lower and upper control limits for the R chart. (You will need a table of control chart factors.) Subgroup Size 2 3 4 5 6 7 8 9

d2 1.128 1.693 2.059 2.326 2.534 2.704 2.847 2.970

D4 3.267 2.574 2.282 2.114 2.004 1.924 1.864 1.816

0 0 0 0 0 0.076 0.136 0.184

A) LCL = 0, UCL = 45.86 B) LCL = 0, UCL = 42.49 C) LCL = 0, UCL = 38.26 D) LCL = 4.48, UCL = 35.58

42) Professor Murphy wants to set up a control chart to monitor the percentage of absenteeism in his introductory statistics course (50 students are registered). Absences per period for the last 15 class sessions are in the table below. Session Absent

1 5

2 0

3 2

4 2

5 3

6 8

7 10

8 3

9 5

10 5

11 1

12 2

13 0

14 2

Calculate the empirical centerline for a p-chart to track absences. Version 1

15 3

A) 0.068 B) 0.072 C) 0.146 D) 0.202

43) Professor Murphy wants to set up a control chart to monitor the percentage of absenteeism in his introductory statistics course (50 students are registered). Absences per period for the last 15 class sessions are in the table below. Session Absent

1 5

2 0

3 2

4 2

5 3

6 8

7 10

8 3

9 5

10 5

11 1

12 2

13 0

14 2

Using 3 sigma limits, calculate lower and upper control limits for a p-chart to track absences. A) 0, 0.252 B) 0, 0.175 C) 0, 0.114 D) −0.038, 0.272

Version 1

15 3

44)

Given the following control chart, which problem is most likely?

A) cycle B) instability C) trend D) level shift E) cycle

45)

Given the following control chart, which problem is most likely?

Version 1

A) instability B) trend C) level shift D) cycle

46)

Given the following control chart, which problem is most likely?

A) instability B) trend C) level shift D) cycle

Version 1

47)

Given the following control chart, which problem is most likely?

A) instability B) trend C) level shift D) cycle

48)

Given the following control chart, which problem is most likely?

Version 1

A) instability B) oscillation C) level shift D) cycle

49)

What does the first letter mean in the Six-Sigma DMAIC acronym?

A) design B) distribute C) describe D) define

50)

What does the second letter mean in the Six-Sigma DMAIC acronym?

A) maximize B) measure C) mentor D) mobilize

51)

What does the third letter mean in the Six-Sigma DMAIC acronym?

A) analyze B) action C) absolve D) attack

52)

What does the fourth letter mean in the Six-Sigma DMAIC acronym?

Version 1

A) integrate B) investigate C) improve D) interact

53)

What does the fifth letter mean in the Six-Sigma DMAIC acronym?

A) cooperate B) correlate C) coordinate D) control

54)

Which is not primarily intended to detect excessive variation in a measurement?

A) s-chart B) MR-chart C) R-chart D) p-chart

55)

Which is most applicable when continuous inspection is used?

A) I-chart B) c-chart C) p-chart D) chart

Version 1

56) If LSL = 500, USL = 518, μ = 509, and σ = 3, the "safety margin" to maintain the product specifications would be

A) nonexistent (i.e., zero). B) 1 σ on each side. C) 2 σ on each side. D) 3 σ on each side.

57) If LSL = 50.00, USL = 56.00, μ = 53.00, and σ = 0.50, the "safety margin" for product specifications would be

A) nonexistent (i.e., zero). B) 1 σ on each side. C) 2 σ on each side. D) 3 σ on each side.

58)

Which is a rule of thumb to indicate an out-of-control process on the chart?

A) single point outside one sigma B) two of three successive points outside one sigma on the same side of the centerline C) four of five successive points on the same side of the centerline D) nine successive points alternating in sign

59)

The Malcolm Baldrige award is awarded annually by the A) American Statistical Association to universities. B) American Society for Quality to individual managers. C) Japanese Society for Quality Control to nonprofit agencies. D) President of the United States to firms.

Version 1

60)

The control chart for a range is intended to measure

A) variation. B) capability. C) skewness. D) trends.

61)

Control limits for a range chart

A) are inappropriate for tracking variation. B) vary cyclically when the mean changes. C) are asymmetric around the centerline. D) show whether the mean has changed.

62) is

Accept-on-Zero plans are spelled out in a Department of Defense standard. This standard

A) MIL-STD-105. B) MIL-STD-1916. C) MIL-STD-2020. D) MIL-STD-250.

63) Quality control refers to methods used by organizations to ensure that their products and services meet customer expectations. ⊚ ⊚

Version 1

true false

64)

An important attribute of quality is conformance to specifications. ⊚ ⊚

65)

Quality includes being reliableor durable but not both. ⊚ ⊚

66)

true false

Quality and productivity are inversely related. ⊚ ⊚

69)

true false

Productivity measures typically compare output to only one factor: labor. ⊚ ⊚

68)

true false

Productivity is measured as the ratio of input to output. ⊚ ⊚

67)

true false

A major goal in statistical quality control is the reduction of variation in a process. ⊚ ⊚

Version 1

true false

70) II.

The Japanese invented and implemented quality control techniques prior to World War

⊚ ⊚

71)

Process control charts were adopted by the Japanese after World War II. ⊚ ⊚

72)

true false

Pareto charts show the frequency of problems that affect a process in descending order. ⊚ ⊚

73)

true false

Statistical process control charts (SPC charts) are attributed to Shewhart. ⊚ ⊚

true false

74) The development of acceptance sampling is attributed to the works of Taguchi and Ishikawa. ⊚ ⊚

75)

true false

An in-control process will always exhibit some common cause variation.

Version 1

⊚ ⊚

76)

true false

Common cause variation does not indicate an out-of-control process. ⊚ ⊚

true false

77) The presence of common cause variation is an indication that the process is out of control. ⊚ ⊚

true false

78) Special cause variation exists when the process produces observations that are not from the same population as the majority of the observations. ⊚ ⊚

79)

true false

Control charts are used to monitor the quality of a product before it is produced. ⊚ ⊚

true false

80) A process may be in a state of control even if one sample mean is more than two standard deviations above the centerline. ⊚ ⊚

Version 1

true false

81) A p-chart is a type of process control chart that can be used for plotting the proportion of nonconforming sampled items. ⊚ ⊚

82)

true false

The Cpk index may indicate a capable process even though the Cp index is unacceptable. ⊚ ⊚

true false

83) A moving range ( MR) chart is appropriate to monitor variation when every single item is being inspected ( n = 1) since the range ( R) cannot be calculated. ⊚ ⊚

true false

84) If a single sample mean is 2.1 standard deviations above the centerline, the process is not in control. ⊚ ⊚

true false

85) ISO 9000 standards were first developed in the United States under the leadership of Joseph Juran. ⊚ ⊚

Version 1

true false

86)

ISO 9000 specifies quality processes rather than defect rates. ⊚ ⊚

87)

Deming stressed identifying the workers who contributed the most to poor quality. ⊚ ⊚

88)

true false

Fishbone diagrams were developed for the Japanese fishing industry. ⊚ ⊚

90)

true false

Deming thought that the majority of quality problems were traceable to faulty equipment. ⊚ ⊚

89)

true false

Service quality can be assessed using a survey called SERVQUAL. ⊚ ⊚

true false

In statistical process control, the Cpk index measures the separate distances between the 91) centerline μ and the USL and LSL. ⊚ ⊚

Version 1

true false

As a rule of thumb, if a process Cpk index is less than 1.00, the level of process capability 92) is usually judged acceptable. ⊚ ⊚

93)

The Cp index equals the Cpk index if USL = 550, LSL = 540, μ = 545, and σ = 0.75. ⊚ ⊚

94)

true false

If USL = 550, LSL = 540, μ = 545, and σ = 1.00, the Cp index is 1.67. ⊚ ⊚

97)

true false

The Cp index equals the Cpk index if USL = 550, LSL = 540, μ = 546, and σ = 1.25. ⊚ ⊚

96)

true false

The Cp index equals the Cpk index if USL = 550, LSL = 540, μ = 543, and σ = 0.75. ⊚ ⊚

95)

true false

If USL = 550, LSL = 540, μ = 545, and σ = 0.4, the process is highly capable.

Version 1

⊚ ⊚

98)

true false

If USL = 550, LSL = 540, μ = 545, and σ = 1.75, the process is highly capable. ⊚ ⊚

true false

99) In general terms, a capable process is one whose variability ( σ) is small in relation to the distance between the centerline μ and the upper and lower specification limits. ⊚ ⊚

true false

100) Management wants a process to be in control and have a capability index at least equal to 1.33 (and ideally much more than 1.33). ⊚ ⊚

true false

101) If you increase the size of the samples taken when using an chart, it is necessary to recalculate your control limits because the limits will be narrower. ⊚ ⊚

true false

102) If you increase the size of the samples taken when using an chart, it is necessary to recalculate your control limits because the limits will be wider. ⊚ ⊚

Version 1

true false

103) The upper and lower control limits of an chart are typically set at plus or minus three standard errors from the centerline. ⊚ ⊚

true false

104) A p-chart is a type of process control chart that is used for plotting the number of defects per unit produced. ⊚ ⊚

105)

true false

A c-chart is based on the Poisson distribution. ⊚ ⊚

true false

106) Quality management is characterized by focus on the customer and continual improvement. ⊚ ⊚

true false

107) A process whose output distribution is stable over time is said to be in statistical control, regardless of whether the desired specifications are being met. ⊚ ⊚

Version 1

true false

108)

A control chart for the mean tells whether the product conforms to specifications. ⊚ ⊚

true false

109) In statistical process control, control charts are used to ensure that a process is stable and in control by detecting special cause variation. ⊚ ⊚

true false

110) Walter Shewhart was an American who studied the control charts that the Japanese had invented after World War II and brought those methods back to the United States during the 1980s. ⊚ ⊚

Version 1

true false

Answer Key Test name: Chap 17_7e_Doane 1) C 2) D 3) C 4) B 5) C 6) D 7) D 8) B 9) D 10) B 11) A 12) D 13) B 14) A 15) C 16) B 17) A 18) B 19) C 20) D 21) B 22) B 23) B 24) D 25) C 26) C Version 1

27) B 28) C 29) A 30) C 31) A 32) A 33) C 34) A 35) B 36) A 37) A 38) B 39) A 40) C 41) C 42) A 43) B 44) D 45) B 46) A 47) D 48) B 49) D 50) B 51) A 52) C 53) D 54) D 55) A 56) A Version 1

57) D 58) A 59) D 60) A 61) C 62) B 63) TRUE 64) TRUE 65) FALSE 66) FALSE 67) FALSE 68) FALSE 69) TRUE 70) FALSE 71) TRUE 72) TRUE 73) TRUE 74) FALSE 75) TRUE 76) TRUE 77) FALSE 78) TRUE 79) FALSE 80) TRUE 81) TRUE 82) FALSE 83) TRUE 84) FALSE 85) FALSE 86) TRUE Version 1

87) FALSE 88) FALSE 89) FALSE 90) TRUE 91) TRUE 92) FALSE 93) TRUE 94) FALSE 95) FALSE 96) TRUE 97) TRUE 98) FALSE 99) TRUE 100) TRUE 101) TRUE 102) FALSE 103) TRUE 104) FALSE 105) TRUE 106) TRUE 107) TRUE 108) FALSE 109) TRUE 110) FALSE

Version 1