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equal_pay___student_wk1.xls
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Data

ID Sal Compa Mid Age EES SER G Raise Deg Gen1 Gr
1 58 1.017 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 0.870 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 34 1.096 31 30 75 5 1 3.6 1 F B
4 66 1.157 57 42 100 16 0 5.5 1 M E The column labels in the table mean:
5 47 0.979 48 36 90 16 0 5.7 1 M D ID – Employee sample number Sal – Salary in thousands
6 76 1.134 67 36 70 12 0 4.5 1 M F Age – Age in years EES – Appraisal rating (Employee evaluation score)
7 41 1.025 40 32 100 8 1 5.7 1 F C SER – Years of service G – Gender (0 = male, 1 = female)
8 23 1.000 23 32 90 9 1 5.8 1 F A Mid – salary grade midpoint Raise – percent of last raise
9 77 1.149 67 49 100 10 0 4 1 M F Grade – job/pay grade Deg (0= BS\BA 1 = MS)
10 22 0.956 23 30 80 7 1 4.7 1 F A Gen1 (Male or Female) Compa - salary divided by midpoint, a measure of salary that removes the impact of grade
11 23 1.000 23 41 100 19 1 4.8 1 F A
12 60 1.052 57 52 95 22 0 4.5 0 M E This data should be treated as a sample of employees taken from a company that has about 1,000
13 42 1.050 40 30 100 2 1 4.7 0 F C employees using a random sampling approach.
14 24 1.043 23 32 90 12 1 6 1 F A
15 24 1.043 23 32 80 8 1 4.9 1 F A
16 47 1.175 40 44 90 4 0 5.7 0 M C Mac Users: The homework in this course assumes students have Windows Excel, and
17 69 1.210 57 27 55 3 1 3 1 F E can load the Analysis ToolPak into their version of Excel.
18 36 1.161 31 31 80 11 1 5.6 0 F B The analysis tool pak has been removed from Excel for Windows, but a free third-party
19 24 1.043 23 32 85 1 0 4.6 1 M A tool that can be used (found on an answers Microsoft site) is:
20 34 1.096 31 44 70 16 1 4.8 0 F B http://www.analystsoft.com/en/products/statplusmacle
21 76 1.134 67 43 95 13 0 6.3 1 M F Like the Microsoft site, I make cannot guarantee the program, but do know that
22 57 1.187 48 48 65 6 1 3.8 1 F D Statplus is a respected statistical package. You may use other approaches or tools
23 23 1.000 23 36 65 6 1 3.3 0 F A as desired to complete the assignments.
24 50 1.041 48 30 75 9 1 3.8 0 F D
25 24 1.043 23 41 70 4 0 4 0 M A
26 24 1.043 23 22 95 2 1 6.2 0 F A
27 40 1.000 40 35 80 7 0 3.9 1 M C
28 75 1.119 67 44 95 9 1 4.4 0 F F
29 72 1.074 67 52 95 5 0 5.4 0 M F
30 49 1.020 48 45 90 18 0 4.3 0 M D
31 24 1.043 23 29 60 4 1 3.9 1 F A
32 28 0.903 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 28 0.903 31 26 80 2 0 4.9 1 M B
35 24 1.043 23 23 90 4 1 5.3 0 F A
36 23 1.000 23 27 75 3 1 4.3 0 F A
37 22 0.956 23 22 95 2 1 6.2 0 F A
38 56 0.982 57 45 95 11 0 4.5 0 M E
39 35 1.129 31 27 90 6 1 5.5 0 F B
40 25 1.086 23 24 90 2 0 6.3 0 M A
41 43 1.075 40 25 80 5 0 4.3 0 M C
42 24 1.043 23 32 100 8 1 5.7 1 F A
43 77 1.149 67 42 95 20 1 5.5 0 F F
44 60 1.052 57 45 90 16 0 5.2 1 M E
45 55 1.145 48 36 95 8 1 5.2 1 F D
46 65 1.140 57 39 75 20 0 3.9 1 M E
47 62 1.087 57 37 95 5 0 5.5 1 M E
48 65 1.140 57 34 90 11 1 5.3 1 F E
49 60 1.052 57 41 95 21 0 6.6 0 M E
50 66 1.157 57 38 80 12 0 4.6 0 M E

Week 2

Week 2 Testing means with the t-test <Note: use right click on row numbers to insert rows to perform analysis below any question>
For questions 2 and 3 below, be sure to list the null and alternate hypothesis statements. Use .05 for your significance level in making your decisions.
For full credit, you need to also show the statistical outcomes - either the Excel test result or the calculations you performed.
1 Below are 2 one-sample t-tests 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?
Males Females
Ho: Mean salary = 45 Ho: Mean salary = 45
Ha: Mean salary =/= 45 Ha: Mean salary =/= 45
Note when performing a one sample test with ANOVA, the second variable (Ho) is listed as the same value for every corresponding value in the data set.
t-Test: Two-Sample Assuming Unequal Variances t-Test: Two-Sample Assuming Unequal Variances
Since the Ho variable has Var = 0, variances are unequal; this test defaults to 1 sample t in this situation
Male Ho Female Ho
Mean 52 45 Mean 38 45
Variance 316 0 Variance 334.6666666667 0
Observations 25 25 Observations 25 25
Hypothesized Mean Difference 0 Hypothesized Mean Difference 0
df 24 df 24
t Stat 1.9689038266 t Stat -1.9132063573
P(T<=t) one-tail 0.0303078503 P(T<=t) one-tail 0.0338621184
t Critical one-tail 1.7108820799 t Critical one-tail 1.7108820799
P(T<=t) two-tail 0.0606157006 P(T<=t) two-tail 0.0677242369
t Critical two-tail 2.0638985616 t Critical two-tail 2.0638985616
Conclusion: Do not reject Ho; mean equals 45 Conclusion: Do not reject Ho; mean equals 45
Interpretation:
2 Based on our sample results, perform a 2-sample t-test to see if the population male and female salaries could be equal to each other.
3 Based on our sample results, can the male and female compas in the population be equal to each other? (Another 2-sample t-test.)
4 What other information would you like to know to answer 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 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?