1. Ashford BUS308 Entire course
Statistics for Managers
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Week One
Required Readings
Chapter 1: An Introduction to Business Statistics
Chapter 2: Descriptive Statistics: Tabular and Graphical Methods
Chapter 3: Descriptive Statistics: Numerical Methods
Discussions
Performance Report. 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.
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.
Quiz
1. Due Day 6.Week One Quiz. Complete the quiz on the assigned readings for
the week.
Assignments
Week One Problems. Complete the following problems from the textbook and
submit them as a Word file.

2. Chapter 1: 1.2, 1.17
Chapter 3: 3.3, 3.22
Week Two
Required Readings
Chapter 4: Probability
Chapter 5: Discrete Random Variables
Chapter 6: Continuous Random Variables
Discussions
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?
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?
Quiz
1. Due Day 6.Week Two Quiz. Complete the quiz on the assigned readings for
the week.
Assignments
Week Two Problems. Complete the following problems from the textbook and
submit them as a Word file. When appropriate, you may use either Excel or
Megastat to complete (see tutorials in chapter appendices).
Chapter 4: 4.4, 4.20, 5.12, 6.22(a)
Chapter 5:
Chapter 6:
Week Three

3. Required Readings
Chapter 7: Sampling and Sampling Distributions
Chapter 8: Confidence Intervals
Discussions
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?
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.
Quiz
1. Due Day 6.Week Three Quiz. Complete the quiz on the assigned readings for
the week.
Assignments
Week Three Problems. Complete the following problems from the textbook and
submit them as a Word file. When appropriate, you may use either Excel or
Megastat to complete (see tutorials in chapter appendices).
Chapter 7: 7.11, 7.30, 8.8, 8.38
Chapter 8:
Week Four
Required Readings
1. Chapter 9: Hypothesis Testing

4. 2. Chapter 12: Chi-Square Tests
Discussions
Hypothesis Test. 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.
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?
Quiz
1. Due Day 6. Week Four Quiz. Complete the quiz on the assigned readings for
the week.
Assignments
Week Four Problems. Complete the following problems from the textbook and
submit them as a Word file. When appropriate, you may use either Excel or
Megastat to complete (see tutorials in chapter appendices).
Chapter 9: 9.13, 9.22
Chapter 12: 12.10, 12.18(a)
WeekFive
Required Readings
1. Chapter 13: Simple Linear Regression Analysis
2. Chapter 15: Process Improvement Using Control Charts (on textbook website:
http://highered.mcgraw-
hill.com/sites/007340182x/student_view0/chapter_15.html)
Discussions

5. 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.
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.
Assignments
Final Project.
Focus of the Final Project
To complete this project, use the “Final Project Data Set” found in your eCollege
classroom in the Final Project description.
Part I:
1. 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
scatterplot and a linear regression line.
3. Answer the following questions using your scatterplot and linear regression
line:
a. What is the slope of the linear regression line?
b. What is the Y-intercept of the linear regression line?
c. What is the equation of the linear regression line in slope-intercept form?
d. Based on the linear regression line, what would be an estimated cost of gas in
the year 2020?
e. What are the residuals of each year?
f. Select a current price that you have seen or paid recently for gas. Is that price
within the range of the linear regression line or is it an outlier? Is it within the
confidence interval of 5% or either end?
Part II:
Imagine that you are a manager at a delivery service and you are creating a
report to project the effects on your company of rising gas prices in the next ten
years. Using the preceding statistical analysis as your basis and outside scholarly
resources to support your claims, write a 3 to 5 page paper interpreting the
results from this perspective. Include the following considerations:

6. 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
where the 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 gas price predictions on the delivery business. Also consider whether or not
you believe your predicted gas prices are accurate. What could occur in the future
that would change your linear regression line and therefore your prediction?