This document provides information about the BUS 308 Statistics for Managers course, including discussion questions, assignments, and data sets used for analyzing gender pay equality. The course uses statistical techniques like descriptive statistics, hypothesis testing, ANOVA, correlation, and regression to analyze a sample employee salary data set. Students apply these methods to examine if gender is impacting pay when considering legal factors like grade, performance reviews, education, etc. The goal is for students to determine if their analyses provide evidence of gender pay inequality or consistency in the population from which the sample was drawn.

1. BUS 308
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BUS 308 STATISTICS FOR MANAGERS ENTIRE
COURSE ( UPDATE COURSE SEPTEMBER 2013)
BUS 308 Week1
DQ 1
Language.
Numbers and measurements are the language of business..Organizations look at results,expenses,quality levels,
efficiencies,time,costs, etc.What measures does y our department keep track of ? How are the measurescollected,
and how are they summarized/described? How are they used in making decisions? (Note: If y ou donot have a job
wheremeasures areavailable toy ou,ask someone you know for some examples or conduct outside research on an
interest of y ours.)
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoof y our classmates by providing
recommendations for the measures being discussed.
DQ 2
Lev els.
Managers and professionals often pay more attention tothe levels of their measures (means,sums,etc.)than tot he
v ariation in the data (thedispersion or the probability patterns/distributions that describethe data).For the
measures you identified in Discussion 1,why must dispersion be considered totruly understandwhat the data is
telling us about what we measure/track? How can we make decisions about outcomes and results if we donot
understand the consistency (variation) of the data? Does looking at the variation in the data give us a different
understanding of results?

2. Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by commenting on the
situations that are being illustrated.
Week 1 Assignment
Problem Set WeekOne.Allstatisticalcalculations willuse the EmployeeSalary Data set (in Appendix
section).
1 . Using the Excel Analysis ToolPakfunction Descriptive Statistics,generate descriptive statistics for the salary data.
Which variables does this function not work properly for,even though we have some generated results?
2. Sort the data by either thevariable G or GEN1 (intomales and females) and find the mean and standard deviation
for each gender for the following variables: SAL, COMPA,AGE, SR, and RAISE. Use Descriptive for one gender and
the fx functions (AVERAGE and STDEV)for the other.
3. What is the probability distribution table for:
a. A randomly selected person being a male in a specificgrade?
b. A randomly selected person being in a specificgrade?
4. Find:
a. The zscore for each malesalary,based on the male salary distribution.
b. The zscore for each female salary, based on thefemale salary distribution.
5. Repeat question 4 for COMPA for each gender.
6. What conclusions can you makeabout theissue of male and femalepay equality? Are all of the results consistent?
If not, why not?
For additional assistance with these calculations reference the Recommended Resources for Week One.
Week 2
DQ 1
t-Tests.
In looking at your business,when and why would you want touse a one-sample mean test (either zor t) or a
twosamplet-test? Create a nulland alternate hypothesis for one of these issues. How would you use the results?

3. Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by commenting on the
potential differences in the results andhow that might affect decision making.
DQ 2
Variation.
Variation exists in virtually allparts of our lives. We often see v ariation 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 andanother,between different production lines, etc.)
between average or actualresults important? How can you or your department decidewhether or not the variation is
important? How could using a mean difference test help?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates and comment on the
use of the test.
Week 2 Assignment
Problem Set WeekTwo.Complete the problems below and submit your workin an Excel document.Be
sure toshow all of y our workandclearly label allcalculations. All statisticalcalculations will use the Employee Salary
Data set (in Appendix section).
Problems
1 . Is either that male or female salary equaltothe overall mean salary? (Twohypotheses, one-sampletests needed.)
2. Are maleand female averagesalaries statistically equaltoeach other?
3. Are themale and female compa averagemeasures equal toeach other?
4. If the salary and compa mean tests in questions 2 and 3 provide different equality results, which would be more
appropriatetouse in answering the question about salary equity? Why?
5. What other information would you like toknow toanswer thequestion about salary equity between the genders?
Why ?
Week 3
DQ 1
ANOVA.

4. In many ways,comparing multiple sample means is simply an extension of what we coveredlast week.What
situations exist where a multiple (more than two) group comparison would be appropriate?(Note: Situationscould
relate toyour work, homelife,socialgroups, etc.).Create a nulland alternate hypothesis for one of these issues. What
would theresults tell you?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by commenting on
why you agree or disagree with the statisticaltest that your peers have described as appropriate in this scenario.
DQ 2
Effect Size
Sev eral statisticaltests havea way tomeasure effect size. What is this,and when might you want touse it in looking at
results from these tests on job related data?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoof y our classmates and…
Week 3 Assignment
Problem Set WeekThree. Complete the problems below and submit your work in an Excel document.
Be sure toshow allof y our workand clearly labelallcalculations.Allstatistical calculations willuse the Employee
Salary Data set (in Appendix section).
1 . Is the average salary the samefor each of the grade levels? (Assume equal variance, and use the Analy sis ToolPak
function ANOVA.)Set up the data input table/range touse as follows:
Put all of the salary values for each grade under theappropriate gradelabel.
A B C D E F
2. The factorial ANOVA with only twovariables can be done with theAnalysis ToolPa kfunction two-way ANOVA with
replication.Set up a data input table like the following:
Grade
Gender A B C D E F
M
F
For each empty cell,randomly pick a maleor female salary from each grade.Interpret theresults.Are the average
salaries for each gender (listedas sample) equal?Are the average salaries for each grade (listed as column)equal?

5. 3. Repeat question 2 for the compa values.
Grade
Gender A B C D E F
M
For each empty cellrandomly picka male or female compa from each grade.Interpret the results. Aretheaverage
compas for each gender (listed as sample)equal? Are theaverage compas for each grade (listed as column)equal?
4. Pick any other variable you are interested in and doa simple two-way ANOVA without replication.Why did you
pick this variable, and what dothe results show?
5. What are your conclusions about salary equity now?
Week 4
DQ 1
Confidence Intervals.
Earlier we discussed issues with looking at only a singlemeasure toassess job-related results.Looking backat the
data examples you have provided in the previous discussion questions on this issue,how might adding confidence
intervals help managers understand results better?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by commenting on
whether or not you think changing the confidence intervals willresult in a different outcome.Explain if you agree or
disagree with the role of a confidence intervalin the interpretation of the answer.
DQ 2
Chi-Square Tests.
Chi-square tests aregreat toshow if distributions differ or if twovariables interact in producing outcomes. What are
some examples of v ariables that you might want tocheck using the chi-square tests? What would these results tell
y ou?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by commenting on
how this information might be used tomakebusiness decisions.
Week 4 Assignment
Problem Set WeekFour.Let’s look at some other factors that might influencepay.Complete the

6. problems below and submit your work in an Excel document.Be suretoshow allof y our workand clearly labelall
calculations.Allstatisticalcalculations willuse the EmployeeSalary Data set (in Appendix section).
1 . Is the probability of having a graduate degree independent of the grade the employee is in?
2. Construct a 95% confidence interval on the mean service for each gender.Dothey intersect?
3. Are males andfemales distributed across grades in a similar pattern?
4. Do95% confidence intervals on the mean length of service for each gender intersect?
5. How do y ou interpret these results in light of our equity question?
Week 5
DQ 1
Correlation.
What results in your departments seem tobe correlated or related toother activities? How could you verify this?
Createa nulland alternatehypothesis for one of these issues. What are the managerial implications of a
correlation between these variables?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by
explaining whether or not you thinkthat there is a relationship between the variables discussed.
DQ 2
Regression.
At times we can generate a regression equation toexplain 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 y ou generated a regression equation,how would you interpret it and the
residuals from it?
Guided Response: Rev iew several of y our classmates’ posts. Respond toat least twoclassmates by commenting on
how this information might be used tomakebusiness decisions.
Week 5
Final Paper

7. The finalassignment for this course is a FinalPaper.The purpose of the FinalPaper is for y ou toculminate the
learning achieved in the course by creating a sales report. The FinalPaper represents 25% of the ov erallcourse grade.
Writing the FinalPaper
Identify an issuein your life (work place,home,socialorganization,etc.)where a statisticalanalysis coul d be used to
help make a managerialdecision.Develop a sampling plan,an appropriate set of hypotheses,and an inferential
statistical procedure totest them.You donot need tocollect any data on this issue, but you will discuss what a
significant statisticaltest would mean and how you would relate this result tothe real-world issue you identified. Your
paper should be three tofive pages in length (excluding the cover and reference pages). In addition tothe text,utilize
at least three sources toto support your points. Noabstract is required.Use the following research plan format to
structurethe paper:
Step 1 : Identification of the problem
Describe what is known about the situation,why it is a concern,and what we donot know.
Step 2: Research Question
What exactly dowe want our study tofindout? This shouldnot be phrased as a yes/noquestion.
Step 3: Data collection
What data is needed toanswer the question,how willwe collect it, and how will wedecide how much we need?
Step 4: Data Analysis
Describe how you would analyze the data.Provide at least one hypothesis test (nulland alternate) and an associated
statistical test.
Step 5: Results andConclusions
Describe how you would interpret the results. For example,what wouldyou recommend if your nullhypothesis was
rejected and what would you doif the nullwas not rejected?
A quick example: Concern if gender is impacting employee’s pay. H0: Gender is not related topay.H1: Gender is
related topay. Approach: Multiple regression equation to see if gender impacts pay after considering thelegalfactors
of grade,appraisal,education,etc.If regression coefficient for gender is significant, will need tocreate residual list t o
see which employees show excessivevariation from predicted salaries when gender is not considered

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BUS 308 WEEK 1 PROBLEM SET WEEK ONE
All statistical calculations will use the Employee Salary Data set (in Appendix section).
1 . Using the Excel Analysis ToolPakor StatPlus:macLE function descriptive statistics,generate and show the
descriptive statistics for each appropriate variable in the sample data set.
a. For which variables in thedata set does this function not workcorrectly for? Why?
2. Sort the data by Gen or Gen 1 (intomales and females) andfind the mean and standard deviation for each gender
for the following variables:
a. sal, compa, age, sr and raise.Use either the descriptive stats function or theFx functions (average and stdev).
3. What is the probability for a:
a. Randomly selectedperson being a male in grade E?
b. Randomly selected male being in grade E?
c. Why are the results different?
4. Find:
a. The zscore for each malesalary,based on only the male salaries.
b. The zscore for each female salary, based on only the female salaries.
c. The zscore for each female compa,based on only the female compa values
d. The zscore for each malecompa,basedon only the male compa values.
e. What dothe distributions and spread suggest about male and female salaries?
f. Why might wewant touse compa tomeasure salaries between males and females?
5. Based on this sample,what conclusions can you make about the issue of male and female pay equality?
6. Are all of the results consistent with your conclusion?If not, why not?
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BUS 308 WEEK 2 PROBLEM SET WEEK TWO
Problem Set WeekTwo.Complete the problems below and submit your workin an Excel document.Be sure toshow
all of y our work and clearly labelall calculations.Allstatistical calculations willuse the Employee Salary Data Set.

9. Included in theWeek Twotab of the EmployeeSalary Data Set are 2 one-sample t-tests comparing male and female
av erage salaries tothe overallsample mean.
1 . Based on our sample,how doy ou interpret theresults and what dothese results suggest about the population
means for male and female salaries?
2. Based on our sample results, perform a 2 -sample t-test tosee if the population male and female salaries could be
equal toeach other.
3. Based on our sample results, can the male and female compas in the population be equal toeach other? (Another 2-
sample t-test.)
4. What other information would you liketoknow toanswer the question about salary equity between the genders?
Why ?
5. If the salary and compa mean tests in questions 3 and 4 provide different results about male andfemale salary
equality, which would be more appropriate touse in answering thequestion about salary equity?Why? What are your
conclusions about equalpay at this point?
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BUS 308 WEEK 3 FINAL OUTLINE DRAFT
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BUS 308 WEEK 3 PROBLEM SET WEEK THREE
Problem Set WeekThree. Complete the problems below and submit your work in an Excel document.Be suretoshow
all of y our work and clearly labelall calculations.All statistical calculations willuse the Employee Salary Data set (in
Appendix section).
1. Based on the sample data,can theaverage(mean) salary in thepopulation be thesame for each of the grade
lev els? (Assumeequalvariance,and use the analysis toolpak or StatPlus:mac LE function ANOVA.)Set up
the input table/range touse as follows: Put allof the salary values for each grade under the appropriate
grade label.Be sure toinclude the null and alternate hypothesis along with the statisticaltest and result.
2. The table and analysis below demonstrate a 2 -way ANOVA with replication.Please interpret the results.
3. Using our sample results,can we say that the compa values in thepopulation are equal by grade and/or
gender,and areindependent of each factor?
4. Pick any other variable you are interested in and doa simple 2 -way ANOVA without replication. Why did
y ou pickthis variable andwhat dothe results show?

10. 5. Using the results for this week, What are your conclusions about gender equalpay for equal workat this
point
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BUS 308 WEEK 4 PROBLEM SET WEEK FOUR
Problem Set WeekFour. Let’s look at some other factors that might influencepay.Complete the
problems below and submit your work in an Excel document.Be suretoshow allof y our workand clearly labelall
calculations.Allstatisticalcalculations willuse the EmployeeSalary Data set (in Appendix section).
1. How do y ou interpret these results in light of our equity question?One question wemight haveis if the
distribution of graduate and undergraduatedegrees independent of the grade theemployee? (Note:this is
the sameas asking if the degrees are distributed thesame way.)Based on theanalysis of our sample data
(shown below),what is your answer?
2. Using our sample data,we can construct a 95% confidence interval for the population’s mean salary for
each gender.Interpret the results. How dothey compare with the findings in the week2 one sample t -test
outcomes (Question 1 )?
3. Based on our sample data,can weconclude that males and females are distributed across grades in a
similar pattern within the population?
4. Using our sample data,construct a 95% confidence interval for the population’s mean servicedifference
for each gender.Dothey intersect or ov erlap? How dothese results comparetothe findings in week2,
question 2?
5. How do y ou interpret these results in light of our question about equalpay for equalwork?
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BUS 308 WEEK 5 FINAL PAPER
The finalassignment for this course is a FinalPaper.The purpose of the FinalPaper is for y ou toculminate the
learning achieved in the course by creating a sales report. The FinalPaper represents 25% of the ov erallcourse grade.
Writing the FinalPaper
Identify an issuein your life (work place,home,socialorganization,etc.)where a statisticalanalysis could be used to
help make a managerialdecision.Develop a sampling plan,an appropriate set of hypotheses,and an inferential
statistical procedure totest them.You donot need tocollect any data on this issue, but you will discuss what a
significant statisticaltest would mean and how you would relate this result tothe real-world issue you identified. Your
paper should be three tofive pages in length (excluding the cover and reference pages). In addition tothe text,utilize

11. at least three sources totosupport your points. Noabstract is required.Use the following research plan format to
structurethe paper:
Step 1 : Identification of the problem
Describe what is known about the situation,why it is a concern,and what we donot know.
Step 2: Research Question
What exactly dowe want our study tofindout? This shouldnot be phrased as a yes/noquestion.
Step 3: Data collection
What data is needed toanswer the question,how willwe collect it, and how will wedecide how much we need?
Step 4: Data Analysis
Describe how you would analyze the data.Provide at least one hypothesis test (nulland alternate) and an associated
statistical test.
Step 5: Results andConclusions
Describe how you would interpret the results. For example,what wouldyou recommend if your nullhypothesis was
rejected and what would you doif the nullwas not rejected?
A quick example: Concern if gender is impacting employee’s pay. H0: Gender is not related topay.H1: Gender is
related topay. Approach: Multiple regression equation tosee if gender impacts pay after considering thelegalfactors
of grade,appraisal,education,etc.If regression coefficient for gender is significant, will need tocreate residual list to
see which employees show excessivevariation from predicted salaries when gender is not considered
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