Question
Employee Number Annual Salary Gender Age (Years) Experience (Years) Training Level 1 32,368 F 42 3 B 2 53,174 M 54 10 B 3 52,722
Employee Number | Annual Salary | Gender | Age (Years) | Experience (Years) | Training Level |
1 | 32,368 | F | 42 | 3 | B |
2 | 53,174 | M | 54 | 10 | B |
3 | 52,722 | M | 47 | 10 | A |
4 | 53,423 | M | 47 | 1 | B |
5 | 50,602 | M | 44 | 5 | B |
6 | 49,033 | M | 42 | 10 | A |
7 | 24,395 | M | 30 | 5 | A |
8 | 24,395 | F | 52 | 6 | A |
9 | 43,124 | M | 48 | 8 | A |
10 | 23,975 | F | 58 | 4 | A |
11 | 53,174 | M | 46 | 4 | C |
12 | 58,515 | M | 36 | 8 | C |
13 | 56,294 | M | 49 | 10 | B |
14 | 49,033 | F | 55 | 10 | B |
15 | 44,884 | M | 41 | 1 | A |
16 | 53,429 | F | 52 | 5 | B |
17 | 46,574 | M | 57 | 8 | A |
18 | 58,968 | F | 61 | 10 | B |
19 | 53,174 | M | 50 | 5 | A |
20 | 53,627 | M | 47 | 10 | B |
21 | 49,033 | M | 54 | 5 | B |
22 | 54,981 | M | 47 | 7 | A |
23 | 62,530 | M | 50 | 10 | B |
24 | 27,525 | F | 38 | 3 | A |
25 | 24,395 | M | 31 | 5 | A |
26 | 56,884 | M | 47 | 10 | A |
27 | 52,111 | M | 56 | 5 | A |
28 | 44,183 | F | 38 | 5 | B |
29 | 24,967 | F | 55 | 6 | A |
30 | 35,423 | F | 47 | 4 | A |
31 | 41,188 | F | 35 | 2 | B |
32 | 27,525 | F | 35 | 3 | A |
33 | 35,018 | M | 39 | 1 | A |
34 | 44,183 | M | 41 | 2 | A |
35 | 35,423 | M | 44 | 1 | A |
36 | 49,033 | M | 53 | 8 | A |
37 | 40,741 | M | 47 | 2 | A |
38 | 49,033 | M | 42 | 10 | A |
39 | 56,294 | F | 44 | 6 | C |
40 | 47,180 | F | 45 | 5 | C |
41 | 46,574 | M | 56 | 8 | A |
42 | 52,722 | M | 38 | 8 | C |
43 | 51,237 | M | 58 | 2 | B |
44 | 53,627 | M | 52 | 8 | A |
45 | 53,174 | M | 54 | 10 | A |
46 | 56,294 | M | 49 | 10 | B |
47 | 49,033 | F | 53 | 10 | B |
48 | 49,033 | M | 43 | 9 | A |
49 | 55,549 | M | 35 | 8 | C |
50 | 51,237 | M | 56 | 1 | C |
51 | 35,200 | F | 38 | 1 | B |
52 | 50,175 | F | 42 | 5 | A |
53 | 24,352 | F | 35 | 1 | A |
54 | 27,525 | F | 40 | 3 | A |
55 | 29,606 | F | 34 | 4 | B |
56 | 24,352 | F | 35 | 1 | A |
57 | 47,180 | F | 45 | 5 | B |
58 | 49,033 | M | 54 | 10 | A |
59 | 53,174 | M | 47 | 10 | A |
60 | 53,429 | F | 45 | 7 | B |
61 | 53,627 | M | 47 | 10 | A |
62 | 26,491 | F | 46 | 7 | A |
63 | 42,961 | M | 36 | 3 | B |
64 | 53,174 | M | 45 | 5 | A |
65 | 37,292 | M | 46 | 0 | A |
66 | 37,292 | M | 47 | 1 | A |
67 | 41,188 | F | 34 | 3 | B |
68 | 57,242 | F | 45 | 7 | C |
69 | 53,429 | F | 44 | 6 | C |
70 | 53,174 | M | 50 | 10 | B |
71 | 44,138 | F | 38 | 2 | B |
Please make an Excel*.
Examine the effect of training level on annual salary, controlling for age and experience factors. For this question, make a dummy variable for training level C vs. not-C to determine if obtaining the highest level of training (level C) increases an employee's expected salary.
1. Report the regression equation and assess the significance and fit of the estimated model: report and interpret the p-value of F-test, the coefficient of determination (R-squared), and the standard error of estimate.
2. Which explanatory variables are statistically significant at 5% level? 3. Interpret the slope coefficient of dummy variable you choose for training level.
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