need help in Statistics for Managers
Problem Set Week One All statistical calculations will use Employee Salary Data Set
1. Using the Excel Analysis ToolPak function descriptive statistics, generate and show the descriptive statistics for each appropriate variable in the sample data set.
1. For which variables in the data set does this function not work correctly for? Why?
2. Sort the data by Gen or Gen 1 (into males and females) and find the mean and standard deviation for each gender for the following variables:
1. sal, compa, age, sr and raise. Use either the descriptive stats function or the Fx functions (average and stdev).
3. What is the probability for a:
1. Randomly selected person being a male in grade E?
2. Randomly selected male being in grade E?
3. Why are the results different?
4. Find:
1. The z score for each male salary, based on only the male salaries.
2. The z score for each female salary, based on only the female salaries.
3. The z score for each female compa, based on only the female compa values.
4. The z score for each male compa, based on only the male compa values.
5. What do the distributions and spread suggest about male and female salaries?
6. Why might we want to use compa to measure 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?
|
ID |
Sal |
Compa |
Mid |
Age |
EES |
SER |
G |
Raise |
Deg |
Gen1 |
Gr |
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1 |
58 |
1.017 |
57 |
34 |
85 |
8 |
0 |
5.7 |
0 |
M |
E |
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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)? |
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2 |
27 |
0.870 |
31 |
52 |
80 |
7 |
0 |
3.9 |
0 |
M |
B |
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Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work. |
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3 |
34 |
1.096 |
31 |
30 |
75 |
5 |
1 |
3.6 |
1 |
F |
B |
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4 |
66 |
1.157 |
57 |
42 |
100 |
16 |
0 |
5.5 |
1 |
M |
E |
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The column labels in the table mean: |
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5 |
47 |
0.979 |
48 |
36 |
90 |
16 |
0 |
5.7 |
1 |
M |
D |
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ID – Employee sample number |
Sal – Salary in thousands |
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6 |
76 |
1.134 |
67 |
36 |
70 |
12 |
0 |
4.5 |
1 |
M |
F |
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Age – Age in years |
EES – Appraisal rating (Employee evaluation score) |
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7 |
41 |
1.025 |
40 |
32 |
100 |
8 |
1 |
5.7 |
1 |
F |
C |
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SER – Years of service |
G – Gender (0 = male, 1 = female) |
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8 |
23 |
1.000 |
23 |
32 |
90 |
9 |
1 |
5.8 |
1 |
F |
A |
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Mid – salary grade midpoint |
Raise – percent of last raise |
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9 |
77 |
1.149 |
67 |
49 |
100 |
10 |
0 |
4 |
1 |
M |
F |
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Grade – job/pay grade |
Deg (0= BS\BA 1 = MS) |
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10 |
22 |
0.956 |
23 |
30 |
80 |
7 |
1 |
4.7 |
1 |
F |
A |
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Gen1 (Male or Female) |
Compa - salary divided by midpoint, a measure of salary that removes the impact of grade |
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11 |
23 |
1.000 |
23 |
41 |
100 |
19 |
1 |
4.8 |
1 |
F |
A |
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12 |
60 |
1.052 |
57 |
52 |
95 |
22 |
0 |
4.5 |
0 |
M |
E |
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This data should be treated as a sample of employees taken from a company that has about 1,000 |
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13 |
42 |
1.050 |
40 |
30 |
100 |
2 |
1 |
4.7 |
0 |
F |
C |
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employees using a random sampling approach. |
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14 |
24 |
1.043 |
23 |
32 |
90 |
12 |
1 |
6 |
1 |
F |
A |
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15 |
24 |
1.043 |
23 |
32 |
80 |
8 |
1 |
4.9 |
1 |
F |
A |
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16 |
47 |
1.175 |
40 |
44 |
90 |
4 |
0 |
5.7 |
0 |
M |
C |
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Mac Users: The homework in this course assumes students have Windows Excel, and |
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17 |
69 |
1.210 |
57 |
27 |
55 |
3 |
1 |
3 |
1 |
F |
E |
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can load the Analysis ToolPak into their version of Excel. |
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18 |
36 |
1.161 |
31 |
31 |
80 |
11 |
1 |
5.6 |
0 |
F |
B |
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The analysis tool pak has been removed from Excel for Windows, but a free third-party |
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19 |
24 |
1.043 |
23 |
32 |
85 |
1 |
0 |
4.6 |
1 |
M |
A |
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tool that can be used (found on an answers Microsoft site) is: |
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20 |
34 |
1.096 |
31 |
44 |
70 |
16 |
1 |
4.8 |
0 |
F |
B |
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21 |
76 |
1.134 |
67 |
43 |
95 |
13 |
0 |
6.3 |
1 |
M |
F |
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Like the Microsoft site, I make cannot guarantee the program, but do know that |
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22 |
57 |
1.187 |
48 |
48 |
65 |
6 |
1 |
3.8 |
1 |
F |
D |
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Statplus is a respected statistical package. |
You may use other approaches or tools |
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23 |
23 |
1.000 |
23 |
36 |
65 |
6 |
1 |
3.3 |
0 |
F |
A |
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as desired to complete the assignments. |
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24 |
50 |
1.041 |
48 |
30 |
75 |
9 |
1 |
3.8 |
0 |
F |
D |
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25 |
24 |
1.043 |
23 |
41 |
70 |
4 |
0 |
4 |
0 |
M |
A |
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26 |
24 |
1.043 |
23 |
22 |
95 |
2 |
1 |
6.2 |
0 |
F |
A |
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27 |
40 |
1.000 |
40 |
35 |
80 |
7 |
0 |
3.9 |
1 |
M |
C |
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28 |
75 |
1.119 |
67 |
44 |
95 |
9 |
1 |
4.4 |
0 |
F |
F |
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29 |
72 |
1.074 |
67 |
52 |
95 |
5 |
0 |
5.4 |
0 |
M |
F |
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30 |
49 |
1.020 |
48 |
45 |
90 |
18 |
0 |
4.3 |
0 |
M |
D |
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31 |
24 |
1.043 |
23 |
29 |
60 |
4 |
1 |
3.9 |
1 |
F |
A |
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32 |
28 |
0.903 |
31 |
25 |
95 |
4 |
0 |
5.6 |
0 |
M |
B |
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33 |
64 |
1.122 |
57 |
35 |
90 |
9 |
0 |
5.5 |
1 |
M |
E |
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34 |
28 |
0.903 |
31 |
26 |
80 |
2 |
0 |
4.9 |
1 |
M |
B |
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35 |
24 |
1.043 |
23 |
23 |
90 |
4 |
1 |
5.3 |
0 |
F |
A |
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36 |
23 |
1.000 |
23 |
27 |
75 |
3 |
1 |
4.3 |
0 |
F |
A |
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37 |
22 |
0.956 |
23 |
22 |
95 |
2 |
1 |
6.2 |
0 |
F |
A |
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38 |
56 |
0.982 |
57 |
45 |
95 |
11 |
0 |
4.5 |
0 |
M |
E |
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39 |
35 |
1.129 |
31 |
27 |
90 |
6 |
1 |
5.5 |
0 |
F |
B |
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40 |
25 |
1.086 |
23 |
24 |
90 |
2 |
0 |
6.3 |
0 |
M |
A |
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41 |
43 |
1.075 |
40 |
25 |
80 |
5 |
0 |
4.3 |
0 |
M |
C |
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42 |
24 |
1.043 |
23 |
32 |
100 |
8 |
1 |
5.7 |
1 |
F |
A |
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43 |
77 |
1.149 |
67 |
42 |
95 |
20 |
1 |
5.5 |
0 |
F |
F |
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44 |
60 |
1.052 |
57 |
45 |
90 |
16 |
0 |
5.2 |
1 |
M |
E |
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45 |
55 |
1.145 |
48 |
36 |
95 |
8 |
1 |
5.2 |
1 |
F |
D |
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46 |
65 |
1.140 |
57 |
39 |
75 |
20 |
0 |
3.9 |
1 |
M |
E |
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47 |
62 |
1.087 |
57 |
37 |
95 |
5 |
0 |
5.5 |
1 |
M |
E |
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48 |
65 |
1.140 |
57 |
34 |
90 |
11 |
1 |
5.3 |
1 |
F |
E |
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49 |
60 |
1.052 |
57 |
41 |
95 |
21 |
0 |
6.6 |
0 |
M |
E |
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50 |
66 |
1.157 |
57 |
38 |
80 |
12 |
0 |
4.6 |
0 |
M |
E |
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