Must be skilled in statistics.

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week_3_excel_homework.xlsx
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Data

ID Salary Compa Midpoint Age Performance Rating Service Gender Raise Degree Gender1 Gr
1 63.9 1.121 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 27.7 0.892 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 34.3 1.105 31 30 75 5 1 3.6 1 F B
4 57.6 1.010 57 42 100 16 0 5.5 1 M E The column labels in the table mean:
5 47.4 0.987 48 36 90 16 0 5.7 1 M D ID – Employee sample number Salary – Salary in thousands
6 75.2 1.122 67 36 70 12 0 4.5 1 M F Age – Age in years Performance Rating - Appraisal rating (employee evaluation score)
7 41.9 1.048 40 32 100 8 1 5.7 1 F C Service – Years of service (rounded) Gender – 0 = male, 1 = female
8 23.4 1.018 23 32 90 9 1 5.8 1 F A Midpoint – salary grade midpoint Raise – percent of last raise
9 74 1.105 67 49 100 10 0 4 1 M F Grade – job/pay grade Degree (0= BS\BA 1 = MS)
10 24.2 1.054 23 30 80 7 1 4.7 1 F A Gender1 (Male or Female) Compa - salary divided by midpoint
11 23.7 1.032 23 41 100 19 1 4.8 1 F A
12 58.3 1.022 57 52 95 22 0 4.5 0 M E
13 41.4 1.034 40 30 100 2 1 4.7 0 F C
14 23.7 1.030 23 32 90 12 1 6 1 F A
15 23 1.001 23 32 80 8 1 4.9 1 F A
16 41.5 1.037 40 44 90 4 0 5.7 0 M C
17 63.6 1.115 57 27 55 3 1 3 1 F E
18 34.3 1.107 31 31 80 11 1 5.6 0 F B
19 24.7 1.073 23 32 85 1 0 4.6 1 M A
20 35.5 1.144 31 44 70 16 1 4.8 0 F B
21 78.1 1.166 67 43 95 13 0 6.3 1 M F
22 49 1.020 48 48 65 6 1 3.8 1 F D
23 23.1 1.005 23 36 65 6 1 3.3 0 F A
24 56.8 1.183 48 30 75 9 1 3.8 0 F D
25 24.2 1.053 23 41 70 4 0 4 0 M A
26 23.1 1.003 23 22 95 2 1 6.2 0 F A
27 45.3 1.132 40 35 80 7 0 3.9 1 M C
28 76.4 1.141 67 44 95 9 1 4.4 0 F F
29 74.6 1.113 67 52 95 5 0 5.4 0 M F
30 48.2 1.005 48 45 90 18 0 4.3 0 M D
31 23.1 1.006 23 29 60 4 1 3.9 1 F A
32 27.8 0.898 31 25 95 4 0 5.6 0 M B
33 61.7 1.083 57 35 90 9 0 5.5 1 M E
34 27.5 0.886 31 26 80 2 0 4.9 1 M B
35 23.7 1.032 23 23 90 4 1 5.3 0 F A
36 25.1 1.093 23 27 75 3 1 4.3 0 F A
37 23.4 1.016 23 22 95 2 1 6.2 0 F A
38 60.1 1.054 57 45 95 11 0 4.5 0 M E
39 36.7 1.184 31 27 90 6 1 5.5 0 F B
40 25.1 1.090 23 24 90 2 0 6.3 0 M A
41 38.8 0.971 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 1.120 67 42 95 20 1 5.5 0 F F
44 64.4 1.129 57 45 90 16 0 5.2 1 M E
45 47.4 0.988 48 36 95 8 1 5.2 1 F D
46 68.7 1.205 57 39 75 20 0 3.9 1 M E
47 59.6 1.045 57 37 95 5 0 5.5 1 M E
48 65.9 1.156 57 34 90 11 1 5.3 1 F E
49 69.1 1.213 57 41 95 21 0 6.6 0 M E
50 65.2 1.143 57 38 80 12 0 4.6 0 M E

Week 3

Week 3 ANOVA Three Questions ID Salary Compa Midpoint Age Performance Rating Service Gender Raise Degree Gender1 Gr Salary Compa
1 63.9 1.121 57 34 85 8 0 5.7 0 M E 23.0 1.001
Remember to show how you got your results in the appropriate cells. For questions using functions, show the input range when asked. 2 27.7 0.892 31 52 80 7 0 3.9 0 M B 23.0 1.001
Group name: G1 G2 G3 G4 G5 G6 3 34.3 1.105 31 30 75 5 1 3.6 1 F B 23.1 1.005
1 One interesting question is are the average compa-ratios equal across salary ranges of 10K each. Salary Intervals: 22-29 30-39 40-49 50-59 60-69 70-79 4 57.6 1.010 57 42 100 16 0 5.5 1 M E 23.1 1.003
While compa-ratios remove the impact of grade on salaries, are they different for different pay levels, Compa-ratio values: 1.001 1.105 1.034 1.183 1.054 1.105 5 47.4 0.987 48 36 90 16 0 5.7 1 M D 23.1 1.006
that is are people at different levels paid differently relative to the midpoint? (Put data values at right.) 1.001 1.107 1.037 1.010 1.083 1.113 6 75.2 1.122 67 36 70 12 0 4.5 1 M F 23.4 1.018
1.005 1.144 1.048 1.022 1.115 1.120 7 41.9 1.048 40 32 100 8 1 5.7 1 F C 23.4 1.016
What is the data input ranged used for this question: 1.003 1.184 1.132 1.045 1.121 1.122 8 23.4 1.018 23 32 90 9 1 5.8 1 F A 23.7 1.032
Step 1: Ho: 1.006 0.971 0.987 1.129 1.141 9 74 1.105 67 49 100 10 0 4 1 M F 23.7 1.030
Ha: 1.018 0.988 1.143 1.166 10 24.2 1.054 23 30 80 7 1 4.7 1 F A 23.7 1.032
Step 2: Decision Rule: 1.016 1.005 1.156 11 23.7 1.032 23 41 100 19 1 4.8 1 F A 24.2 1.054
Step 3: Statistical test: 1.032 1.020 1.205 12 58.3 1.022 57 52 95 22 0 4.5 0 M E 24.2 1.053
Why? 1.030 1.213 13 41.4 1.034 40 30 100 2 1 4.7 0 F C 24.7 1.073
Step 4: Conduct the test - place cell b16 in the output location box. 1.032 14 23.7 1.030 23 32 90 12 1 6 1 F A 25.1 1.093
Anova: Single Factor 1.054 15 23 1.001 23 32 80 8 1 4.9 1 F A 25.1 1.090
1.053 16 41.5 1.037 40 44 90 4 0 5.7 0 M C 27.5 0.886
SUMMARY 1.073 17 63.6 1.115 57 27 55 3 1 3 1 F E 27.7 0.892
Groups Count Sum Average Variance 1.093 18 34.3 1.107 31 31 80 11 1 5.6 0 F B 27.8 0.898
22-29 18 18.183 1.0101666667 0.0038003824 1.090 19 24.7 1.073 23 32 85 1 0 4.6 1 M A 34.3 1.105
30-39 5 5.511 1.1022 0.0064207 0.886 20 35.5 1.144 31 44 70 16 1 4.8 0 F B 34.3 1.107
40-49 8 8.251 1.031375 0.0021594107 0.892 21 78.1 1.166 67 43 95 13 0 6.3 1 M F 35.5 1.144
50-59 4 4.26 1.065 0.0063993333 0.898 22 49 1.020 48 48 65 6 1 3.8 1 F D 36.7 1.184
60-69 9 10.219 1.1354444444 0.0026730278 23 23.1 1.005 23 36 65 6 1 3.3 0 F A 38.8 0.971
70-79 6 6.767 1.1278333333 0.0004933667 24 56.8 1.183 48 30 75 9 1 3.8 0 F D 41.4 1.034
25 24.2 1.053 23 41 70 4 0 4 0 M A 41.5 1.037
26 23.1 1.003 23 22 95 2 1 6.2 0 F A 41.9 1.048
ANOVA 27 45.3 1.132 40 35 80 7 0 3.9 1 M C 45.3 1.132
Source of Variation SS df MS F P-value F crit 28 76.4 1.141 67 44 95 9 1 4.4 0 F F 47.4 0.987
Between Groups 0.1383651494 5 0.0276730299 8.2019441989 0.0000154421 2.4270401198 29 74.6 1.113 67 52 95 5 0 5.4 0 M F 47.4 0.988
Within Groups 0.1484542306 44 0.0033739598 30 48.2 1.005 48 45 90 18 0 4.3 0 M D 48.2 1.005
31 23.1 1.006 23 29 60 4 1 3.9 1 F A 49.0 1.020
Total 0.28681938 49 32 27.8 0.898 31 25 95 4 0 5.6 0 M B 56.8 1.183
Step 5: Conclusions and Interpretation 33 61.7 1.083 57 35 90 9 0 5.5 1 M E 57.6 1.010
What is the p-value? 0.0000154421 34 27.5 0.886 31 26 80 2 0 4.9 1 M B 58.3 1.022
35 23.7 1.032 23 23 90 4 1 5.3 0 F A 59.6 1.045
Is P-value < 0.05? 36 25.1 1.093 23 27 75 3 1 4.3 0 F A 60.1 1.054
37 23.4 1.016 23 22 95 2 1 6.2 0 F A 61.7 1.083
What is your decision: REJ or NOT reject the null? 38 60.1 1.054 57 45 95 11 0 4.5 0 M E 63.6 1.115
39 36.7 1.184 31 27 90 6 1 5.5 0 F B 63.9 1.121
If the null hypothesis was rejected, what is the effect size value (eta squared)? 40 25.1 1.090 23 24 90 2 0 6.3 0 M A 64.4 1.129
41 38.8 0.971 40 25 80 5 0 4.3 0 M C 65.2 1.143
If calculated, what does the effect size value tell us about why the null hypothesis was rejected? 42 23 1.001 23 32 100 8 1 5.7 1 F A 65.9 1.156
43 75 1.120 67 42 95 20 1 5.5 0 F F 68.7 1.205
What does that decision mean in terms of our equal pay question? 44 64.4 1.129 57 45 90 16 0 5.2 1 M E 69.1 1.213
45 47.4 0.988 48 36 95 8 1 5.2 1 F D 74.0 1.105
46 68.7 1.205 57 39 75 20 0 3.9 1 M E 74.6 1.113
2 If the null hypothesis in question 1 was rejected, which pairs of means differ? Why? 47 59.6 1.045 57 37 95 5 0 5.5 1 M E 75.0 1.120
48 65.9 1.156 57 34 90 11 1 5.3 1 F E 75.2 1.122
Groups Compared Diff T +/- Term Low to High Difference Significant? Why? 49 69.1 1.213 57 41 95 21 0 6.6 0 M E 76.4 1.141
G1 G2 50 65.2 1.143 57 38 80 12 0 4.6 0 M E 78.1 1.166
G1 G3
G1 G4
G1 G5
G1 G6
G2 G3
G2 G4
G2 G5
G2 G6
G3 G4
G3 G5
G3 G6
G4 G5
G4 G6
G5 G6
3 Since compa is already a measure of pay for equal work, do these results impact
your conclusion on equal pay for equal work? Why or why not?