This document describes performing a regression analysis using compa as the dependent variable and the same independent variables as a previous analysis. It provides the regression hypotheses and asks to interpret the findings, including the F statistic value, its p-value and whether it is significant. It also asks for the coefficient p-values, whether they are significant, and which variables are significant. It concludes by asking for the regression equation using only significant variables and whether gender is a significant factor in determining compa.

1. Question 3)
Perform a regression analysis using compa as the dependent variable and the same independent
variables as used in question 2. (Question #2 found below the table). Show the result, and
interpret your findings by answering the same questions.
Note: be sure to include the appropriate hypothesis statements.
A ) Regression hypotheses
Ho:
Ha:
Coefficient hyhpotheses (one to stand for all the separate variables)
Ho:
Ha:
B )Interpretation:
For the Regression as a whole:
What is the value of the F statistic:
What is the p-value associated with this value:
Is the p-value < 0.05?
Do you reject or not reject the null hypothesis:
What does this decision mean for our equal pay question (Do M and F get paid equaly?):
C )For each of the coefficients: Intercept, Midpoint, Age, Perf. rating, Service, Gender, Degree
What is the coefficient's p-value for each of the variables:
Is the p-value < 0.05?
Do you reject or not reject each null hypothesis:
What are the coefficients for the significant variables?
Using only the significant variables, what is the equation? Compa =
Is gender a significant factor in compa:
If so, who gets paid more with all other things being equal?
How do we know?
ID
Salary
Compa
Midpoint
Age
Performance Rating
Service
Gender

2. Raise
Degree
Gender1
Gr
1
66.1
1.159
57
34
85
8
0
5.7
0
M
E
2
25.9
0.834
31
52
80
7
0
3.9
0
M
B
3
35.2
1.135
31
30
75
5
1

3. 3.6
1
F
B
4
55.3
0.971
57
42
100
16
0
5.5
1
M
E
5
49.6
1.033
48
36
90
16
0
5.7
1
M
D
6
78.3
1.168
67
36
70
12
0

4. 4.5
1
M
F
7
42.3
1.058
40
32
100
8
1
5.7
1
F
C
8
22.8
0.990
23
32
90
9
1
5.8
1
F
A
9
78
1.164
67
49
100
10
0

5. 4
1
M
F
10
23.3
1.014
23
30
80
7
1
4.7
1
F
A
11
23.6
1.025
23
41
100
19
1
4.8
1
F
A
12
60.8
1.067
57
52
95
22
0

6. 4.5
0
M
E
13
40.6
1.014
40
30
100
2
1
4.7
0
F
C
14
21.7
0.943
23
32
90
12
1
6
1
F
A
15
21.8
0.949
23
32
80
8
1

7. 4.9
1
F
A
16
37.4
0.934
40
44
90
4
0
5.7
0
M
C
17
57
1.000
57
27
55
3
1
3
1
F
E
18
33.5
1.081
31
31
80
11
1

8. 5.6
0
F
B
19
23
1.000
23
32
85
1
0
4.6
1
M
A
20
36
1.162
31
44
70
16
1
4.8
0
F
B
21
76
1.135
67
43
95
13
0

9. 6.3
1
M
F
22
43.7
0.911
48
48
65
6
1
3.8
1
F
D
23
25.3
1.098
23
36
65
6
1
3.3
0
F
A
24
48.9
1.019
48
30
75
9
1

10. 3.8
0
F
D
25
25.8
1.122
23
41
70
4
0
4
0
M
A
26
23.3
1.013
23
22
95
2
1
6.2
0
F
A
27
42.3
1.057
40
35
80
7
0

11. 3.9
1
M
C
28
75.2
1.122
67
44
95
9
1
4.4
0
F
F
29
80.9
1.208
67
52
95
5
0
5.4
0
M
F
30
49
1.020
48
45
90
18
0

12. 4.3
0
M
D
31
24.2
1.054
23
29
60
4
1
3.9
1
F
A
32
27.5
0.886
31
25
95
4
0
5.6
0
M
B
33
63.6
1.115
57
35
90
9
0

13. 5.5
1
M
E
34
28.6
0.922
31
26
80
2
0
4.9
1
M
B
35
22.4
0.976
23
23
90
4
1
5.3
0
F
A
36
23.6
1.026
23
27
75
3
1

14. 4.3
0
F
A
37
24.3
1.057
23
22
95
2
1
6.2
0
F
A
38
63
1.105
57
45
95
11
0
4.5
0
M
E
39
34.8
1.123
31
27
90
6
1

15. 5.5
0
F
B
40
24.3
1.057
23
24
90
2
0
6.3
0
M
A
41
42.8
1.071
40
25
80
5
0
4.3
0
M
C
42
23
0.998
23
32
100
8
1

16. 5.7
1
F
A
43
75.4
1.125
67
42
95
20
1
5.5
0
F
F
44
60.7
1.065
57
45
90
16
0
5.2
1
M
E
45
57.9
1.206
48
36
95
8
1

17. 5.2
1
F
D
46
62.2
1.091
57
39
75
20
0
3.9
1
M
E
47
62.2
1.091
57
37
95
5
0
5.5
1
M
E
48
70.1
1.230
57
34
90
11
1

18. 5.3
1
F
E
49
61.7
1.083
57
41
95
21
0
6.6
0
M
E
50
61.4
1.077
57
38
80
12
0
4.6
0
M
E
Question 2)
Below is a regression analysis for salary being predicted/explained by the other variables in our
sample (Midpoint, age, performance rating, service, gender, and degree variables. (Note: since
salary and compa are different ways of expressing an employee’s salary, we do not want to have
both used in the same regression.)
Plase interpret the findings. ( Note: technically we have one for each input variable. Listing it
this way to save space.)
Ho: The regression equation is not significant.

19. Ha: The regression equation is significant.
Ho: The regression coefficient for each variable is not significant
Ha: The regression coefficient for each variable is significant
Sal
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.991559074655531
R Square
0.983189398531733
Adjusted R Square
0.98084373321058
Standard Error
2.65759257261024
Observations
50
ANOVA
df
SS
MS
F
Significance F
Regression
6
17762.2996738743
2960.38327897905
419.151611129353
0.0000000000000000000000000000000000018121523852609
Residual
43
303.700326125705
7.06279828199313
Total
49
18066
Coefficients

20. Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Lower 95.0%
Upper 95.0%
Intercept
-1.74962121233985
3.61836765827431
-0.48353881572507
0.631166489854994
-9.04675504271989
5.54751261804019
-9.04675504271989
5.54751261804019
Midpoint
1.21670105053015
0.0319023509083532
38.1382881163022
0.0000000000000000000000000000000000866416336978111
1.15236382831625
1.28103827274406
1.15236382831625
1.28103827274406
Age
-0.00462801024512803
0.0651972120227729
-0.0709847875628716
0.943738987458078
-0.136110719142857
0.126854698652601
-0.136110719142857
0.126854698652601
Performace Rating
-0.0565964405497542

21. 0.0344950678086454
-1.64071109712588
0.108153181882588
-0.126162374711284
0.0129694936117759
-0.126162374711284
0.0129694936117759
Service
-0.0425003573420269
0.0843369820842078
-0.503935003265728
0.616879351918047
-0.212582091217666
0.127581376533612
-0.212582091217666
0.127581376533612
Gender
2.42033721201279
0.860844317571592
2.81158528041454
0.00739661875026853
0.684279192016561
4.15639523200902
0.684279192016561
4.15639523200902
Degree
0.275533414317469
0.799802304805058
0.344501900859896
0.732148118953479
-1.33742165470733
1.88848848334226
-1.33742165470733
1.88848848334226
Note: Since Gender and Degree are expressed as 0 and 1, they are considered dummy variables
and can be used in multiple regression equations

22. ID
Salary
Compa
Midpoint
Age
Performance Rating
Service
Gender
Raise
Degree
Gender1
Gr
1
66.1
1.159
57
34
85
8
0
5.7
0
M
E
2
25.9
0.834
31
52
80
7
0
3.9
0
M
B

23. 3
35.2
1.135
31
30
75
5
1
3.6
1
F
B
4
55.3
0.971
57
42
100
16
0
5.5
1
M
E
5
49.6
1.033
48
36
90
16
0
5.7
1
M
D

24. 6
78.3
1.168
67
36
70
12
0
4.5
1
M
F
7
42.3
1.058
40
32
100
8
1
5.7
1
F
C
8
22.8
0.990
23
32
90
9
1
5.8
1
F
A

25. 9
78
1.164
67
49
100
10
0
4
1
M
F
10
23.3
1.014
23
30
80
7
1
4.7
1
F
A
11
23.6
1.025
23
41
100
19
1
4.8
1
F
A

26. 12
60.8
1.067
57
52
95
22
0
4.5
0
M
E
13
40.6
1.014
40
30
100
2
1
4.7
0
F
C
14
21.7
0.943
23
32
90
12
1
6
1
F
A

27. 15
21.8
0.949
23
32
80
8
1
4.9
1
F
A
16
37.4
0.934
40
44
90
4
0
5.7
0
M
C
17
57
1.000
57
27
55
3
1
3
1
F
E

28. 18
33.5
1.081
31
31
80
11
1
5.6
0
F
B
19
23
1.000
23
32
85
1
0
4.6
1
M
A
20
36
1.162
31
44
70
16
1
4.8
0
F
B

29. 21
76
1.135
67
43
95
13
0
6.3
1
M
F
22
43.7
0.911
48
48
65
6
1
3.8
1
F
D
23
25.3
1.098
23
36
65
6
1
3.3
0
F
A

30. 24
48.9
1.019
48
30
75
9
1
3.8
0
F
D
25
25.8
1.122
23
41
70
4
0
4
0
M
A
26
23.3
1.013
23
22
95
2
1
6.2
0
F
A

31. 27
42.3
1.057
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
80.9
1.208
67
52
95
5
0
5.4
0
M
F

32. 30
49
1.020
48
45
90
18
0
4.3
0
M
D
31
24.2
1.054
23
29
60
4
1
3.9
1
F
A
32
27.5
0.886
31
25
95
4
0
5.6
0
M
B

33. 33
63.6
1.115
57
35
90
9
0
5.5
1
M
E
34
28.6
0.922
31
26
80
2
0
4.9
1
M
B
35
22.4
0.976
23
23
90
4
1
5.3
0
F
A

34. 36
23.6
1.026
23
27
75
3
1
4.3
0
F
A
37
24.3
1.057
23
22
95
2
1
6.2
0
F
A
38
63
1.105
57
45
95
11
0
4.5
0
M
E

35. 39
34.8
1.123
31
27
90
6
1
5.5
0
F
B
40
24.3
1.057
23
24
90
2
0
6.3
0
M
A
41
42.8
1.071
40
25
80
5
0
4.3
0
M
C

36. 42
23
0.998
23
32
100
8
1
5.7
1
F
A
43
75.4
1.125
67
42
95
20
1
5.5
0
F
F
44
60.7
1.065
57
45
90
16
0
5.2
1
M
E

37. 45
57.9
1.206
48
36
95
8
1
5.2
1
F
D
46
62.2
1.091
57
39
75
20
0
3.9
1
M
E
47
62.2
1.091
57
37
95
5
0
5.5
1
M
E

38. 48
70.1
1.230
57
34
90
11
1
5.3
1
F
E
49
61.7
1.083
57
41
95
21
0
6.6
0
M
E
50
61.4
1.077
57
38
80
12
0
4.6
0
M
E

39. Solution