Week 1 Problem Set

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Week1ProblemSet.xlsx
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Sheet1

ID Salary Compa-ratio Midpoint Age Performance Rating Service Gender Raise Degree Gender1 Grade Do not manipuilate Data set on this page, copy to another page to make changes
1 62.5 1.096 57 34 85 8 0 5.7 0 M E The ongoing question that the weekly assignments will focus on is: Are males and females paid the same for equal work (under the Equal Pay Act)?
2 27.8 0.897 31 52 80 7 0 3.9 0 M B Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
3 35.9 1.158 31 30 75 5 1 3.6 1 F B
4 65.4 1.147 57 42 100 16 0 5.5 1 M E The column labels in the table mean:
5 49.1 1.023 48 36 90 16 0 5.7 1 M D ID – Employee sample number Salary – Salary in thousands
6 75.6 1.129 67 36 70 12 0 4.5 1 M F Age – Age in years Performance Rating - Appraisal rating (employee evaluation score)
7 40.2 1.005 40 32 100 8 1 5.7 1 F C Service – Years of service (rounded) Gender – 0 = male, 1 = female
8 23.3 1.013 23 32 90 9 1 5.8 1 F A Midpoint – salary grade midpoint Raise – percent of last raise
9 78.5 1.171 67 49 100 10 0 4 1 M F Grade – job/pay grade Degree (0= BS\BA 1 = MS)
10 22.9 0.997 23 30 80 7 1 4.7 1 F A Gender1 (Male or Female) Compa-ratio - salary divided by midpoint
11 24.2 1.050 23 41 100 19 1 4.8 1 F A
12 64 1.122 57 52 95 22 0 4.5 0 M E
13 40.8 1.021 40 30 100 2 1 4.7 0 F C
14 24.1 1.046 23 32 90 12 1 6 1 F A
15 23.8 1.034 23 32 80 8 1 4.9 1 F A
16 40.9 1.023 40 44 90 4 0 5.7 0 M C
17 66.5 1.167 57 27 55 3 1 3 1 F E
18 35.2 1.136 31 31 80 11 1 5.6 0 F B
19 23.9 1.039 23 32 85 1 0 4.6 1 M A
20 33.5 1.080 31 44 70 16 1 4.8 0 F B
21 74.2 1.107 67 43 95 13 0 6.3 1 M F
22 55.8 1.162 48 48 65 6 1 3.8 1 F D
23 23 1.001 23 36 65 6 1 3.3 0 F A
24 55.9 1.164 48 30 75 9 1 3.8 0 F D
25 25 1.085 23 41 70 4 0 4 0 M A
26 22.6 0.983 23 22 95 2 1 6.2 0 F A
27 46.3 1.157 40 35 80 7 0 3.9 1 M C
28 75.2 1.122 67 44 95 9 1 4.4 0 F F
29 77.8 1.161 67 52 95 5 0 5.4 0 M F
30 45.6 0.949 48 45 90 18 0 4.3 0 M D
31 22.8 0.991 23 29 60 4 1 3.9 1 F A
32 28.7 0.927 31 25 95 4 0 5.6 0 M B
33 64 1.122 57 35 90 9 0 5.5 1 M E
34 27.9 0.899 31 26 80 2 0 4.9 1 M B
35 23.8 1.034 23 23 90 4 1 5.3 0 F A
36 22.7 0.987 23 27 75 3 1 4.3 0 F A
37 23.7 1.032 23 22 95 2 1 6.2 0 F A
38 60.7 1.065 57 45 95 11 0 4.5 0 M E
39 36.2 1.169 31 27 90 6 1 5.5 0 F B
40 24.3 1.058 23 24 90 2 0 6.3 0 M A
41 41.4 1.035 40 25 80 5 0 4.3 0 M C
42 23 1.001 23 32 100 8 1 5.7 1 F A
43 75.7 1.130 67 42 95 20 1 5.5 0 F F
44 61 1.071 57 45 90 16 0 5.2 1 M E
45 54.8 1.141 48 36 95 8 1 5.2 1 F D
46 62 1.087 57 39 75 20 0 3.9 1 M E
47 61 1.071 57 37 95 5 0 5.5 1 M E
48 71.6 1.257 57 34 90 11 1 5.3 1 F E
49 60.6 1.063 57 41 95 21 0 6.6 0 M E
50 57.7 1.012 57 38 80 12 0 4.6 0 M E

Sheet2

Week 1: Descriptive Statistics, including Probability
While the lectures will examine our equal pay question from the compa-ratio viewpoint, our weekly assignments will focus on
examining the issue using the salary measure.
The purpose of this assignmnent is two fold:
1. Demonstrate mastery with Excel tools.
2. Develop descriptive statistics to help examine the question.
3. Interpret descriptive outcomes
The first issue in examining salary data to determine if we - as a company - are paying males and females equally for doing equal work is to develop some
descriptive statistics to give us something to make a preliminary decision on whether we have an issue or not.
1 Descriptive Statistics: Develop basic descriptive statistics for Salary
The first step in analyzing data sets is to find some summary descriptive statistics for key variables.
Suggestion: Copy the gender1 and salary columns from the Data tab to columns T and U at the right.
Then use Data Sort (by gender1) to get all the male and female salary values grouped together.
a. Use the Descriptive Statistics function in the Data Analysis tab Place Excel outcome in Cell K19
to develop the descriptive statistics summary for the overall
group's overall salary. (Place K19 in output range.)
Highlight the mean, sample standard deviation, and range.
b. Using Fx (or formula) functions find the following (be sure to show the formula
and not just the value in each cell) asked for salary statistics for each gender:
Male Female
Mean:
Sample Standard Deviation:
Range:
2 Develop a 5-number summary for the overall, male, and female SALARY variable.
For full credit, show the excel formulas in each cell rather than simply the numerical answer.
Overall Males Females
Max
3rd Q
Midpoint
1st Q
Min
3 Location Measures: comparing Male and Female midpoints to the overall Salary data range.
For full credit, show the excel formulas in each cell rather than simply the numerical answer.
Using the entire Salary range and the M and F midpoints found in Q2 Male Female
a. What would each midpoint's percentile rank be in the overall range? Use Excel's =PERCENTRANK.EXC function
b. What is the normal curve z value for each midpoint within overall range? Use Excel's =STANDARDIZE function
4 Probability Measures: comparing Male and Female midpoints to the overall Salary data range
For full credit, show the excel formulas in each cell rather than simply the numerical answer.
Using the entire Salary range and the M and F midpoints found in Q2, find Male Female
a. The Empirical Probability of equaling or exceeding (=>) that value for Show the calculation formula = value/50 or =countif(range,">="&cell)/50
b. The Normal curve Prob of => that value for each group Use "=1-NORM.S.DIST" function
5 Conclusions: What do you make of these results? Be sure to include findings from this week's lectures as well.
In comparing the overall, male, and female outcomes, what relationship(s) see, to exist between the data sets?
What does this suggest about our equal pay for equal work question?