BUS 308 OUTLET Dreams Come True /bus308outlet.com

Page 1

BUS 308 Entire Course (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com BUS 308 Week 1 Assignment Problems 1.2, 1.17, 3.3 & 3.22 BUS 308 Week 1 DQ 1 Performance Report BUS 308 Week 1 DQ 2 The Empirical Rule vs. Chebyshev Theorem BUS 308 Week 1 Quiz (10 MCQ) BUS 308 Week 2 Assignments Problems 4.4, 4.20, 5.12, 6.22(a) BUS 308 Week 2 DQ 1 Relative Frequency BUS 308 Week 2 DQ 2 Applications for Probability BUS 308 Week 2 Quiz (10 MCQ) BUS 308 Week 3 Assignments Problems 7.11, 7.30, 8.8, 8.38 BUS 308 Week 3 DQ 1 Unscientific Sampling BUS 308 Week 3 DQ 2 Article Review BUS 308 Week 3 Quiz (10 MCQ) BUS 308 Week 4 Assignments Problems 9.13, 9.22, 12.10, 12.18(a) BUS 308 Week 4 DQ 1 Hypothesis Test BUS 308 Week 4 DQ 2 Creating Hypotheses BUS 308 Week 4 Quiz (10 MCQ) BUS 308 Week 5 DQ 1 Linear Correlation BUS 308 Week 5 DQ 2 Quality Control BUS 308 Week 5 Final Part I - Excel BUS 308 Week 5 Final Part II Analysis Paper on gas prices **********************************************************************************

BUS 308 Entire Course (New)

FOR MORE CLASSES VISIT www.bus308outlet.com

BUS 308 Week 1 DQ 1 Data Scales BUS 308 Week 1 DQ 2 Probability BUS 308 Week 1 Quiz BUS 308 Week 1 Problem Set Week One BUS 308 Week 2 Journal BUS 308 Week 2 DQ 1 t-Tests BUS 308 Week 2 DQ 2 ANOVA Testing BUS 308 Week 2 Quiz BUS 308 Week 2 Problem Set BUS 308 Week 3 DQ 1 Interval Data BUS 308 Week 3 DQ 2 Correlation BUS 308 Week 3 Assignment Evaluation of Correlations BUS 308 Week 4 DQ 1 Simple Regression Analysis BUS 308 Week 4 DQ 2 Multiple Regressions Analysis BUS 308 Week 4 Problem Set BUS 308 Week 4 Quiz BUS 308 Week 5 DQ 1 Confidence Intervals BUS 308 Week 5 DQ 2 Correlation and Confidence Intervals BUS 308 Week 5 Final Paper **********************************************************************************

BUS 308 Week 1 Assignment Problems 1.2, 1.17, 3.3 and 3.22 (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com BUS 308 Week 1 Problems 1.2, 1.17, 3.3 and 3.22 **********************************************************************************

BUS 308 Week 1 DQ 1 Language

FOR MORE CLASSES VISIT

www.bus308outlet.com Discussion 1-1/Language Numbers and measurements are the language of business. Organizations look at results in many ways: expenses, quality levels, efficiencies, time, costs, etc. What measures does your department keep track of? Are they descriptive or inferential data, and what is the difference between these? (Note: If you do not have a job where measures are available to you, ask someone you know for some examples, or conduct outside research on an interest of yours, or use personal measures.) **********************************************************************************

BUS 308 Week 1 DQ 1 Performance Report (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com You are the manager at a company and are asked to present a report on the year-to-date performance of your division. What type of statistical information would you include in your report? In particular, which descriptive statistics (mean, median, standard deviation, etc.) do you think would best represent the main aspects of the performance of your division? What types of graphical presentation (histogram, dot plot, stem-and-leaf, bar chart, etc.) would you include? Explain your reasoning

**********************************************************************************

BUS 308 Week 1 DQ 2 Probability

FOR MORE CLASSES VISIT www.bus308outlet.com Things vary in life – virtually nothing (except physical standards such as the speed of light) we interact with is constant over time. Much of this variation follows somewhat predictable patterns that can be examined using probability. An example of a subjective probability is: “Cops usually do not patrol this road, so I can get away with speeding.” An empirical probability example is: “Each production run has a 5% reject rate.” A classical (or theoretical) probability example is: “This die has six sides, so I should see the number 2 come up 1/6th of the time.” What are some examples of probability outcomes in your work or life? How would looking at them in terms of probabilities help us understand what is going on? How does the normal curve relate to activities/things you are associated with? **********************************************************************************

BUS 308 Week 1 DQ 2 The Empirical Rule vs. Chebyshev Theorem (Ash Course)

FOR MORE CLASSES VISIT

www.bus308outlet.com The Empirical Rule vs. Chebyshev’s Theorem Discuss how the Empirical Rule works and how it relates to the bell curve as illustrated in Figure 3.14 (a). Then, explain Chebyshev’s Theorem and how it is different from the Empirical Rule. Give a specific example of a population with which the Empirical Rule might be most effective and one with which Chebyshev’s Theorem might be most effective. Respond to at least two of your classmates’ postings. **********************************************************************************

BUS 308 Week 1 Problem Set

FOR MORE CLASSES VISIT www.bus308outlet.com 1. For assistance with these calculations, see the Recommended Resources for Week One. Measurement issues. Data, even numerically code variables, can be one of 4 levels – nominal, ordinal, interval, or ratio. It is important to identify which level a variable is, as this impacts the kind of analysis we can do with the data. For example, descriptive statistics such as means can only be done on interval or ratio level data. Please list, under each label, the variables in our data set that belong in each group..

2. The first step in analyzing data sets is to find some summary descriptive statistics for key variables. For salary, compa, age, Performance Rating, and Service; find the mean and standard deviation for 3 groups: overall sample, Females, and Males. You can use either the Data Analysis Descriptive Statistics tool or the Fx =average and =stdev functions. Note: Place data to the right, if you use Descriptive statistics, place that to the right as well: 3. What is the probability for a: a. Randomly selected person being a male in grade E? b. Randomly selected male being in grade E? c. Why are the results different? 4. For each group (overall, females, and males) find:: a. The value that cuts off the top 1/3 salary in each group. b. The z score for each value. c. The normal curve probability of exceeding this score. d. What is the empirical probability of being at or exceeding this salary value? e. The score that cuts off the top 1/3 compa in each group. f. The z score for each value. g. The normal curve probability of exceeding this score. h. What is the empirical probability of being at or exceeding this salary value?

i. How do you interpret the relationship between the data sets? What do they mean about our equal pay for equal work question? 5. Equal Pay Conclusions: a. What conclusions can you make about the issue of male and male pay equality? Are all of the results consistent? b. What is the difference between the salary and compa measures of pay? c. Conclusions from looking at salary results: d. Conclusions from looking at compa results: e. Do both salary measures show the same results? f. Can we make any conclusions about equal pay for equal work yet? **********************************************************************************

BUS 308 Week 1 Quiz

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : Data on the city from which members of a board of directors come represent interval data. 2. Question : samples.

Inferential statistics infer the characteristics of

3.

The mode is which of the following?

Question :

4. Question : The standard error of the mean can be calculated by dividing μ by the square root of the number of values in the distribution. 5. Question : If a certifying agency raises the requirements for real estate agents, what sort of decision error is the agency protecting against? 6. Question : significance?

Which of the following defines statistical

7. Question : In a frequency distribution such as a bellshaped curve, what does the vertical height of the curve indicate? 8. Question : Which of the following is a provision of the central limit theorem? 9. 10.

Question : Question :

In statistical notation, M is to μ as s is to σ. Technically, “statistic” refers to which?

**********************************************************************************

BUS 308 Week 1 Quiz (10 MCQ) (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : The two types of quantitative variables are

2. Question : As a general rule, when creating a stem-and-leaf display, there should be between ______ stem values.

3. Question : The median is the value below which and above which approximately 50 percent of the measurements lie.

4. Question : Temperature in degrees Fahrenheit is an example of a ____ variable.

5. Question : Stem-and-leaf displays and dot plots are useful for detecting

6. Question : Any characteristic of a population unit is called a

7. Question : The science of using a sample to make generalizations about the important aspects of a population is known as

8. Question : A normal population has 99.73 percent of the population measurements within ___ standard deviations of the mean.

9. Question : When we are choosing a random sample and we do not place chosen units back into the population, we are

10. Question : An example of manipulation of graphical display used to distort reality is:

**********************************************************************************

BUS 308 Week 1 Quiz (New)

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : In statistical notation, M is to Îź as s is to Ďƒ. Question 2. Question : A parameter refers to a sample characteristic.

Question 3. Question : Data on the city from which members of a board of directors come represent interval data.

Question 4. Question : In a frequency distribution such as a bellshaped curve, what does the vertical height of the curve indicate?

Question 5. Question : The z transformation makes data normal.

Question 6. Question : Data on the ages of customers are ratio scale data.

Question 7. Question : A probability is found by dividing the number of possible outcomes (o) by the number of successes â‚Ź = o/e.

Question 8. Question : The z-score indicates where an individual data value lies within the data set.

Question 9. Question : The standard deviation of normally distributed data sets is equal to about 1/6 of the data set’s range.

Question 10. Question : The probability of two independent events occurring together equals the product of each of the individual event probabilities.

**********************************************************************************

BUS 308 Week 2 Assignments Problems 4.4, 4.20, 5.12, 6.22(a) (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com BUS 308 Week 2 Assignments Problems 4.4, 4.20, 5.12, 6.22(a) **********************************************************************************

BUS 308 Week 2 DQ 1 Hypotheses

FOR MORE CLASSES VISIT www.bus308outlet.com Discussion 2-1/Hypotheses

What is a hypothesis test? Why do we need to use them to make decisions about relating sample results to the population; why can’t we just make our decisions by the sample value? **********************************************************************************

BUS 308 Week 2 DQ 1 Relative Frequency (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com

Relative Frequency. Conceptually we would expect the probability of newborn males and females to be the same. However, census reports indicate that the ratios of males and females in various countries do not conform to the theoretical prediction. What do you think accounts for this variation? Can you think of other cases where the expected probabilities do not quite agree with the empirical values? **********************************************************************************

BUS 308 Week 2 DQ 2 Applications for Probability (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Applications for Probability. In what situations might you use probability as a manager to approach business-related problems? What are the advantages to using probability concepts in business decisions? Are there any disadvantages or possible pitfalls to avoid in using probability in business? **********************************************************************************

BUS 308 Week 2 DQ 2 Variation

FOR MORE CLASSES VISIT www.bus308outlet.com Variation exists in virtually all parts of our lives.

We often see variation in results in what we spend (utility costs each month, food costs, business supplies, etc.). Consider the measures and data you use (in either your personal or job activities). When are differences (between one time period and another, between different production lines, etc.) between average or actual results important? How can you or your department decide whether or not the observed differences over time are important? How could using a mean difference test help? **********************************************************************************

BUS 308 Week 2 Problem Set

FOR MORE CLASSES VISIT www.bus308outlet.com Problem Set Week Two Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the Included in the Week Two tab of theEmployee Salary Data Set are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean.

1. Below are 2 one-sample t-test comparing male and female average salaries to the overall sample mean. Based on our sample, how do you interpret the results and what do these results suggest about the population means for male and female salaries? 2. Based on our sample data set, perform a 2-sample t-test to see if the population male and female average salaries could be equal to each other. (Since we have not yet covered testing for variance equality, assume the data sets have statistically equal variances.) 3. Based on our sample data set, can the male and female compas in the population be equal to each other? (Another 2sample t-test.) 4. Since performance is often a factor in pay levels, is the average Performance Rating the same for both genders? 5. If the salary and compa mean tests in questions 2 and 3 provide different results about male and female salary equality, which would be more appropriate to use in answering the question about salary equity? Why? What are your conclusions about equal pay at this point?? **********************************************************************************

BUS 308 Week 2 Quiz

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : How is the sum of squares unlike either the standard deviation or the variance?

2. Question : If sums of squares statistics are calculated for shoppers at three different retail outlets, what statistic will indicate the variability among those at each outlet? 3. Question : ANOVA?

Which is the symbol used for the test statistic in

4. Question : If ANOVA reveals that four different departments have significantly different levels of productivity, what will a post-hoc test indicate? 5. Question : distribution?

The independent t-test is based on which

6.

What does omega-squared indicate?

Question :

7. Question : of the following?

Each different t-distribution is defined by which

8. Question : When a significant interaction is graphed, what is indicated on the vertical axis? 9. Question : Four different groups of employees are randomly selected from a common population for a study of differences in the impact of a wage increase. Why will there be differences even before the incentive is applied? 10. Question : What is the probability of type II error when the null hypothesis is rejected? **********************************************************************************

BUS 308 Week 2 Quiz (10 MCQ) (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com

1. Question : In a statistical study, the random variable X = 1, if the house is colonial, and X = 0 if the house is not colonial, then it can be stated that the random variable is continuous.

2. Question : The set of all possible experimental outcomes is called a(n)

3. Question : If two events are independent, then the probability of their intersection is represented by:

4. Question : A(n) __________ is a measure of the chance that an uncertain event will occur.

5. Question : The price-to-earning ratio for firms in a given industry is distributed according to normal distribution. In this industry, a firm with a Z value equal to 1

6. Question : The expected value of a discrete random variable is:

7. Question : For a continuous distribution, P(a ≤ X ≤ b) = P(a <X< b).

8. Question : The following formula: P(A U B) = P(A) + P(B) - P(A ∩ B) represents

9. Question : The MPG (mileage per gallon) for a mid-size car is normally distributed with a mean of 32 and a standard deviation of .8. What is the probability that the MPG for a selected mid-size car would be less than 33.2?

10. Question : The height of a continuous probability curve over a given point is **********************************************************************************

BUS 308 Week 2 Quiz (New)

FOR MORE CLASSES VISIT www.bus308outlet.com

1. Question : What is the relationship between the power of a statistical test and decision errors?

Question 2. Question : The desired sample depends on all of these factors except?

Question 3. Question : What question does the z test answer?

Question 4. Question : The desired sample size depends only the size of the population to be tested.

Question 5. Question : Each different t-distribution is defined by which of the following?

Question 6. Question : What is the alternate hypothesis in a problem where sales group two is predicted to be “. . . significantly less productive than sales group one?�

Question 7. Question : Why do the critical values change with degrees of freedom for the t-tests?

Question 8. Question : If a certifying agency raises the requirements for real estate agents, what sort of decision error is the agency protecting against?

Question 9. Question : The desired sample size depends only the size of the population to be tested.

Question 10. Question : The z- test requires an estimate of the population standard deviation.

**********************************************************************************

BUS 308 Week 3 Assignments Problems 7.11, 7.30, 8.8, 8.38 (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com BUS 308 Week 3 Assignments Problems 7.11, 7.30, 8.8, 8.38 **********************************************************************************

BUS 308 Week 3 DQ 1 ANOVA

FOR MORE CLASSES VISIT www.bus308outlet.com In many ways, comparing multiple sample means is simply an extension of what we covered last week.

Just as we had 3 versions of the t-test (1 sample, 2 sample (with and without equal variance), and paired; we have several versions of ANOVA – single factor, factorial (called 2-factor with replication in Excel), and withinsubjects (2-factor without replication in Excel). What examples (professional, personal, social) can you provide on when we might use each type? What would be the appropriate hypotheses statements for each example? **********************************************************************************

BUS 308 Week 3 DQ 1 Unscientific Sampling (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Unscientific Sampling. Consider question 7.45 from the text: A Milwaukee television station, WITI-TV, conducted a telephone call-in survey asking whether viewers liked the new newspaper, the Journal Sentinel. On April 26, 1995, Tim Cuprisin, a columnist for the Journal Sentinel, wrote the following comment: “WITI-TV (Channel 6) did one of those polls—which they admit are unscientific—last week and found that 388 viewers like the new Journal Sentinel and 2,629 didn’t like it. We did our own unscientific poll on whether those Channel 6 surveys accurately reflect public opinion. The results: a full 100 percent of the respondents say absolutely, positively not.” Is Cuprisin’s comment justified? **********************************************************************************

BUS 308 Week 3 DQ 2 Article Review (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Article Review. Many articles present statistical data and list margins of error (for example, reports on political opinion polls, growth or decline of the housing markets, manufacturing sectors, etc.). Find one such article from a reliable source (such as EBSCO or Proquest) in the online library that includes a construction of confidence intervals for the data studied, and give a summary of the topic and the statistical results presented. In particular, discuss whether there is enough information presented in the article to arrive at the same conclusion as reported **********************************************************************************

BUS 308 Week 3 DQ 2 Effect Size

FOR MORE CLASSES VISIT www.bus308outlet.com Several statistical tests have a way to measure effect size. What is this, and when might you want to use it in looking at results from these tests on job related data? **********************************************************************************

BUS 308 Week 3 Problem Set

FOR MORE CLASSES VISIT www.bus308outlet.com

ASSIGNMENT WEEK 3

Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the (Note: Questions 1- 4 have additional elements to respond to below the analysis results.) 1. Last week, we found that the average performance ratings do not differ between males and females in the population. Now we need to see if they differ among the grades. Is the average performance rating the same for all grades? (Assume variances are equal across the grades for this ANOVA.) 2. While it appears that average salaries per grade differ, we need to test this assumption. Is the average salary the same for each of the grade levels? (Assume equal variances, and use the Analysis toolpak function ANOVA.) Use the input table to the right to list salaries under each grade level. 3. The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results. 4. Many companies consider the midpoint to be the “market rate” – what is needed to hire a new employee. Does the company, on average, pay its existing employees at or above the market rate? 5. Using the results through this week, what are your conclusions about gender equal pay for equal work at this point? **********************************************************************************

BUS 308 Week 3 Quiz (10 MCQ) (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : There is little difference between the values of ta/2 and Za/2 when the sample

2. Question : If the population proportion is .4 with a sample size of 20, then is this sample large enough so that the sampling distribution of is a normal distribution.

3. Question : For non-normal populations, as the sample size (n) _________, the distribution of sample means approaches a/an __________ distribution.

4. Question : As the sample size ________the variation of the sampling distribution of ___________.

5. Question : Assuming the same value of a, as the sample size increases, the value of ta/2 approaches the value of Za/2.

6. Question : If the sampled population has mean 48 and standard deviation 16, then the mean and the standard deviation for the sampling distribution of for n = 16 are

7. Question : The sampling distribution of x bar must be a normal distribution with a mean 0 and standard deviation 1.

8. Question : As our sample standard deviation increases when all other parts of the confidence interval stay the same, then the confidence interval will become:

9. Question : When the sample size and sample standard deviation remain the same, a 99% confidence interval for a population mean, Âľ will be _____ the 95% confidence interval for Âľ.

10. Question : A manufacturing company measures the weight of boxes before shipping them to the customers. If the box weights have

a population mean and standard deviation of 90 lbs and 24 lbs respectively, then, based on a sample size of 36 boxes, the probability that the average weight of the boxes will be less than 84 lbs is **********************************************************************************

BUS 308 Week 4 Assignments Problems 9.13, 9.22, 12.10, 12.18(a) (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com BUS 308 Week 4 Assignments Problems 9.13, 9.22, 12.10, 12.18(a) **********************************************************************************

BUS 308 Week 4 DQ 1 Confidence Intervals

FOR MORE CLASSES VISIT www.bus308outlet.com Discussion 4-1/Confidence Intervals Many people do not “like” or “trust” single point estimates for things they need measured. Looking back at the data examples you have provided in the previous discussion questions on this issue, how might adding confidence intervals help managers accept the results better? Why?

Ask a manger in your organization if they would prefer a single point estimate or a range for important measures, and why? Please share what they say. **********************************************************************************

BUS 308 Week 4 DQ 1 Hypothesis Test (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Give an example of a hypothesis test you could perform at work or at home. State what the Null and the Alternative hypotheses would be in your test. Explain how you would settle on a reasonable level of significance for your scenario. Also explain what the type I and II errors would be if you reached the incorrect conclusion in your test. **********************************************************************************

BUS 308 Week 4 DQ 2 Chi-Square Tests

FOR MORE CLASSES VISIT www.bus308outlet.com Discussion 4-2/Chi-Square Tests Chi-square tests are great to show if distributions differ or if two variables interact in producing outcomes. What are some examples of variables that you might want to check using the chi-square tests? What would these results tell you? **********************************************************************************

BUS 308 Week 4 DQ 2 Creating Hypotheses (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Creating Hypotheses. Assume you are the manager of a paint manufacturing factory. Your company has received complaints from customers that the containers hold less than the amount printed on them. On the other hand, corporate management is concerned that the containers hold more than the standard amount. You assign a statistician to verify these claims. A sample of containers was selected and the volume of paint in each container was measured. Assuming that the volume printed on each container is 1 gallon, how would you formulate the null and alternative hypotheses to test the customers’ claim? As a manager, what reasonable criteria will you use to set a value for the level of significance to be used in the test? After answering this question, what type of error would you suppose may result in that case? **********************************************************************************

BUS 308 Week 4 Problem Set

FOR MORE CLASSES VISIT www.bus308outlet.com ASSIGNMENT WEEK 4 Let’s look at some other factors that might influence pay. Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the

1. Using our sample data, construct a 95% confidence interval for the population's mean salary for each gender. Interpret the results. How do they compare with the findings in the week 2 one sample t-test outcomes (Question 1)? 2. Using our sample data, construct a 95% confidence interval for the mean salary difference between the genders in the population. How does this compare to the findings in week 2, question 2? 3. We found last week that the degrees compa values within the population. Do not impact compa rates. This does not mean that degrees are distributed evenly across the grades and genders. Do males and females have the same distribution of degrees by grade? 4. Based on our sample data, can we conclude that males and females are distributed across grades in a similar pattern within the population? 5. How do you interpret these results in light of our question about equal pay for equal work? **********************************************************************************

BUS 308 Week 4 Quiz

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : With reference to problem 1, what statistic determines the correlation of experience with productivity, controlling for age in experience?

2. Question : In a problem where interest rates and growth of the economy are used to predict consumer spending, which of the following will increase prediction error? 3. Question : With reference to problem 3, how is the regression constant or the a value interpreted? 4. Question : regression?

Which of the following is a problem in simple

5. Question : In a problem where average temperature and number of daylight hours are used to predict energy consumption in homes, what does the standard error of multiple estimate gauge? 6. Question : What does “shrinkage� mean in reference to regression solutions? 7. Question : The degree to which years of education and years of experience together correlate with annual salary is indicated in multiple correlation. 8. Question : The criterion variable in regression is the variable used to predict the value of y. 9. Question : Which of the following are consistent with the requirements of simple regression? 10. Question : the estimate.

Larger sample diminish the standard error of

**********************************************************************************

BUS 308 Week 4 Quiz (10 MCQ) (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com

1. Question : Consider using p-value to test H0 versus Ha by setting α equal to .10. We reject H0 at level α of significance if and only if the p-value is:

2. Question : When carrying out a sample test (with ó known) of H0: µ = 10 vs. Ha: µ > 10 by using a rejection point, we reject Ho at level of significance a if and only if the calculated test statistic is

3. Question : When using the chi-square goodness of fit test, if the value of the chi-square statistic is large enough, we reject the null hypothesis.

4. Question : The actual counts in the cells of a contingency table are referred to as the expected cell frequencies.

5. Question : For a hypothesis test about a population mean or proportion, if the level of significance is less than the p-value, the null hypothesis is rejected.

6. Question : When we carry out a chi-square test for independence, the null hypothesis states that the two relevant classifications

7. Question : The manager of the quality department for a tire manufacturing company wants to study the average tensile strength of rubber used in making a certain brand of radial tire. The population is normally distributed and the population standard deviation is known. She uses a Z test to test the null hypothesis that the mean tensile strength is less than or equal to 800 pounds per square inch. The calculated Z test Statistic is a positive value that leads to a pvalue of .067 for the test. If the significance level is .10, the null hypothesis would be rejected.

8. Question : A type II error is failing to reject a false null hypothesis.

9. Question : For the chi-square goodness of fit test, the rejection point X2a is in

10. Question : If a null hypothesis is not rejected at a significance level of .05, it will ______ be rejected at a significance level of .01. **********************************************************************************

BUS 308 Week 4 Quiz (New)

FOR MORE CLASSES VISIT www.bus308outlet.com 1. Question : The goodness of fit test null hypothesis states that the sample data does not match an expected distribution.

Question 2. Question : Statistical significance in the Chi-square test means the population distribution (expected) is not the source of the sample (observed) data.

Question 3. Question : While rejecting the null hypothesis for the goodness of fit test means distributions differ, rejecting the null for the test of independence means the variables interact.

Question 4. Question : The null hypothesis for the test of independence states that no correlation exists between the variables.

Question 5. Question : For a one sample confidence interval, the interval is calculated around the calculated sample mean (m).

Question 6. Question : For a one sample confidence interval, if the interval contains the Οm , the corresponding t-test will have a statistically significant result – rejecting the null hypothesis.

Question 7. Question : The distribution for the goodness of fit test equals k-1, where k equals the number of categories.

Question 8. Question : Chi-square tests rarely have type I errors.

Question 9. Question : Confidence intervals provide an indication of how much variation exists in the data set.

Question 10. Question : The Chi-square test is very sensitive to small differences in frequency differences. **********************************************************************************

BUS 308 Week 5 DQ 1 Correlation

FOR MORE CLASSES VISIT www.bus308outlet.com Discussion 5-1/Correlation

What results in your departments seem to be correlated or related to other activities? How could you verify this? Create a null and alternate hypothesis for one of these issues. What are the managerial implications of a correlation between these variables? **********************************************************************************

BUS 308 Week 5 DQ 1 Linear Correlation (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Linear Correlation. Do you think there is a correlation between CEO salaries and the degree of success of a company? If you were to take a sample of companies with comparable size, market capitalization, and product category, and plot CEO salaries against the net profit of their respective companies, do you expect to find a linear correlation between the two? Explain **********************************************************************************

BUS 308 Week 5 DQ 2 Quality Control (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Quality Control. Visit the websites on Quality Control (QC) listed in the Required Websites for this week. In addition, locate an article on

the Internet or in the Library databases that describes an example of the use of statistics in Quality Control. In your post, briefly define Quality Control and explain its importance. Also, describe some of the most widely used tools in the industry for measuring and controlling quality, emphasizing their relationship to what you have encountered in this class. Finally, explain the example from your article of statistics as applied in a Quality Control context. **********************************************************************************

BUS 308 Week 5 DQ 2 Regression

FOR MORE CLASSES VISIT www.bus308outlet.com Discussion 5-2/Regression At times we can generate a regression equation to explain outcomes. For example, an employee’s salary can often be explained by their pay grade, appraisal rating, education level, etc. What variables might explain or predict an outcome in your department or life? If you generated a regression equation, how would you interpret it and the residuals from it? **********************************************************************************

BUS 308 Week 5 Final Paper (2 Papers)

FOR MORE CLASSES VISIT www.bus308outlet.com

This tutorial contains 2 Different Papers

The final paper provides you with an opportunity to integrate and reflect on what you have learned during the class. The question to address is: “What have you learned about statistics?” In developing your responses, consider – at a minimum – and discuss the application of each of the course elements in analyzing and making decisions about data (counts and/or measurements). The course elements include: · Descriptive statistics · Inferential statistics · Hypothesis development and testing · Selection of appropriate statistical tests · Evaluating statistical results. Writing the Final Paper The Final Paper: 1. Must be three to- five double-spaced pages in length, and formatted according to APA style as outlined in the Ashford Writing Center. 2. Must include a title page with the following: a. Title of paper

b. Student’s name c. Course name and number d. Instructor’s name e. Date submitted 3. Must begin with an introductory paragraph that has a succinct thesis statement. 4. Must address the topic of the paper with critical thought. 5. Must end with a conclusion that reaffirms your thesis. 6. Must use at least three scholarly sources, in addition to the text. 7. Must document all sources in APA style, as outlined in the Ashford Writing Center. 8. Must include a separate reference page, formatted according to APA style as outlined in the Ashford Writing Center. **********************************************************************************

BUS 308 Week 5 Final Part I - Excel (Ash Course)

FOR MORE CLASSES VISIT www.bus308outlet.com Calculate the mean yearly value using the average gas prices by month found in the"Final Project Data Set". 2.Using the years as your x-axis and the annual mean as your y-axis, create a scatterplotand a linear regression line.

3.Answer the following questions using your scatterplot and linear regression line:* What is the slope of the linear regression line?* What is the Y-intercept of the linear regression line?*

What is the equation of the linear regression line, in slope-intercept form?* Based on the linear regression line, what would be an estimated cost of gas in the year2020?* What are the residuals of each year?* Select a current price that you have seen or paid recently for gas. Is that price within therange of the linear regression line or is it an outlier? Is it within the confidence interval of5% or either end? **********************************************************************************

BUS 308 Week 5 Final Part II Analysis Paper on gas prices

FOR MORE CLASSES VISIT www.bus308outlet.com Imagine that you are a manager at a delivery service and you are creating a report toproject the effects on your company of rising gas prices in the next ten years. Using thepreceding statistical analysis as your basis and outside scholarly resources to support yourclaims, write a 3 to 5 page paper interpreting the results from this perspective. Include thefollowing considerations:

1. Introduce the project and its significance to the company.

2. Explain the statistical analysis that you completed in Part I. Be sure to explain wherethe data came from, what analysis was done, and what the results were.

3. Give conclusions that you have drawn from the data. Consider the effects of your gasprice predictions on the delivery business. Also consider whether or not you believe yourpredicted gas prices are accurate. What could occur in the future that would change yourlinear regression line and therefore your prediction? **********************************************************************************

BUS 308 Week 5 Problem Set

FOR MORE CLASSES VISIT www.bus308outlet.com ASSIGNMENT WEEK 5

1. Create a correlation table for the variables in our (Use analysis ToolPak or StatPlus:mac LE function Correlation).

a. Reviewing the data levels from week 1, what variables can be used in a Pearson’s Correlation Table (which is what Excel produces)? b. Place the table here. c. Using r= approximately .28 as the significant r value (at p = .05) for a correlation between 50 values, what variables are significantly related to salary? To compa? d. Looking at the above correlations – both significant or not – are there any surprises – by that I mean any relationships you expected to be meaningful and are not, and vice-versa? e. Does this information help us answer our equal pay for equal work question? 2. Below is a regression analysis for salary being predicted/explained by the other variables in our sample (Midpoint, age, performance rating, service, raise, and degree variables). Note: since salary and compa are different ways of expressing an employee’s salary, we do not want to have both used in the same regression. Please interpret the findings. 3. Perform a regression analysis using compa as the dependent variable and the same independent variables as used in question 2. Show the result, and interpret your findings by answering the same questions. Note: be sure to include the appropriate hypothesis statements. 4. Based on all of your results to date, is gender a factor in the pay practices of this company? If so, which gender gets paid more? How do we know? Which is the best variable to use in analyzing pay practices - salary or compa? Why? What is the

most interesting or surprising thing about the results we got doing the analyses during the last 5 weeks? 5. Why did the single factor tests and analysis (such as t and single factor ANOVA tests on salary equality) not provide a complete answer to our salary equality question? What outcomes in your life or work might benefit from a multiple regression examination rather than a simpler one variable test? **********************************************************************************

Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.