A large firm employing tens of thousands of workers has been accused of discriminating against its
female managers. The accusation is based on a random sample of 40 managers. The mean annual salary of the 20 female managers is $79,500 while the mean annual salary of the 20 male managers is $103,250. The president of the firm points out that the company has a strict policy of equal pay for equal work and that the difference may be due to other variables. Accordingly, he found and recorded the number of years of education and the number of years of experience for each of the 40 managers in the sample. Also recorded are the salary and gender (1 = female and 0 = male). The data are in attached Excel document. The president wanted to know whether a regression analysis would shed some light on the issue.
Use Microsoft Excel to run a regression of annual salary on years of education, years of experience, and gender and round up numbers in your regression results to 2 decimal points. Please use the level of significance of 10 percent (i.e. α = 0.10). On the basis of your Excel results answer following questions.
Interpret the numerical value of adjusted R-square.
Annual Salary(in $1000.00) |
Education(in years) |
Experience(in years) |
Gender |
130 |
20 |
18 |
0 |
80 |
19 |
16 |
1 |
62 |
18 |
8 |
1 |
176 |
18 |
30 |
0 |
44 |
14 |
9 |
1 |
139 |
16 |
22 |
0 |
165 |
18 |
27 |
0 |
112 |
19 |
20 |
1 |
92 |
16 |
17 |
1 |
84 |
18 |
13 |
1 |
106 |
14 |
17 |
0 |
103 |
22 |
24 |
1 |
98 |
16 |
18 |
0 |
93 |
17 |
14 |
1 |
79 |
16 |
14 |
1 |
92 |
16 |
14 |
0 |
79 |
14 |
16 |
0 |
98 |
20 |
18 |
1 |
111 |
19 |
25 |
1 |
45 |
15 |
10 |
0 |
82 |
16 |
13 |
0 |
100 |
19 |
21 |
1 |
88 |
15 |
15 |
0 |
76 |
18 |
13 |
1 |
123 |
16 |
21 |
0 |
120 |
17 |
22 |
0 |
50 |
18 |
7 |
1 |
30 |
17 |
4 |
1 |
135 |
16 |
19 |
0 |
84 |
14 |
17 |
0 |
50 |
16 |
6 |
1 |
65 |
15 |
9 |
0 |
83 |
17 |
12 |
1 |
105 |
21 |
21 |
1 |
70 |
17 |
10 |
1 |
99 |
15 |
12 |
0 |
89 |
18 |
8 |
0 |
93 |
15 |
14 |
0 |
68 |
17 |
11 |
1 |
57 |
15 |
10 |
0 |
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