Question
Employee Number Annual Salary Gender Gender dummy Age (Years) Experience (Years) Training Level Training dummy 1 32,368 F 0 42 3 B 1 2 53,174
Employee Number | Annual Salary | Gender | Gender dummy | Age (Years) | Experience (Years) | Training Level | Training dummy |
1 | 32,368 | F | 0 | 42 | 3 | B | 1 |
2 | 53,174 | M | 1 | 54 | 10 | B | 1 |
3 | 52,722 | M | 1 | 47 | 10 | A | 1 |
4 | 53,423 | M | 1 | 47 | 1 | B | 1 |
5 | 50,602 | M | 1 | 44 | 5 | B | 1 |
6 | 49,033 | M | 1 | 42 | 10 | A | 1 |
7 | 24,395 | M | 1 | 30 | 5 | A | 1 |
8 | 24,395 | F | 0 | 52 | 6 | A | 1 |
9 | 43,124 | M | 1 | 48 | 8 | A | 1 |
10 | 23,975 | F | 0 | 58 | 4 | A | 1 |
11 | 53,174 | M | 1 | 46 | 4 | C | 0 |
12 | 58,515 | M | 1 | 36 | 8 | C | 0 |
13 | 56,294 | M | 1 | 49 | 10 | B | 1 |
14 | 49,033 | F | 0 | 55 | 10 | B | 1 |
15 | 44,884 | M | 1 | 41 | 1 | A | 1 |
16 | 53,429 | F | 0 | 52 | 5 | B | 1 |
17 | 46,574 | M | 1 | 57 | 8 | A | 1 |
18 | 58,968 | F | 0 | 61 | 10 | B | 1 |
19 | 53,174 | M | 1 | 50 | 5 | A | 1 |
20 | 53,627 | M | 1 | 47 | 10 | B | 1 |
21 | 49,033 | M | 1 | 54 | 5 | B | 1 |
22 | 54,981 | M | 1 | 47 | 7 | A | 1 |
23 | 62,530 | M | 1 | 50 | 10 | B | 1 |
24 | 27,525 | F | 0 | 38 | 3 | A | 1 |
25 | 24,395 | M | 1 | 31 | 5 | A | 1 |
26 | 56,884 | M | 1 | 47 | 10 | A | 1 |
27 | 52,111 | M | 1 | 56 | 5 | A | 1 |
28 | 44,183 | F | 0 | 38 | 5 | B | 1 |
29 | 24,967 | F | 0 | 55 | 6 | A | 1 |
30 | 35,423 | F | 0 | 47 | 4 | A | 1 |
31 | 41,188 | F | 0 | 35 | 2 | B | 1 |
32 | 27,525 | F | 0 | 35 | 3 | A | 1 |
33 | 35,018 | M | 1 | 39 | 1 | A | 1 |
34 | 44,183 | M | 1 | 41 | 2 | A | 1 |
35 | 35,423 | M | 1 | 44 | 1 | A | 1 |
36 | 49,033 | M | 1 | 53 | 8 | A | 1 |
37 | 40,741 | M | 1 | 47 | 2 | A | 1 |
38 | 49,033 | M | 1 | 42 | 10 | A | 1 |
39 | 56,294 | F | 0 | 44 | 6 | C | 0 |
40 | 47,180 | F | 0 | 45 | 5 | C | 0 |
41 | 46,574 | M | 1 | 56 | 8 | A | 1 |
42 | 52,722 | M | 1 | 38 | 8 | C | 0 |
43 | 51,237 | M | 1 | 58 | 2 | B | 1 |
44 | 53,627 | M | 1 | 52 | 8 | A | 1 |
45 | 53,174 | M | 1 | 54 | 10 | A | 1 |
46 | 56,294 | M | 1 | 49 | 10 | B | 1 |
47 | 49,033 | F | 0 | 53 | 10 | B | 1 |
48 | 49,033 | M | 1 | 43 | 9 | A | 1 |
49 | 55,549 | M | 1 | 35 | 8 | C | 0 |
50 | 51,237 | M | 1 | 56 | 1 | C | 0 |
51 | 35,200 | F | 0 | 38 | 1 | B | 1 |
52 | 50,175 | F | 0 | 42 | 5 | A | 1 |
53 | 24,352 | F | 0 | 35 | 1 | A | 1 |
54 | 27,525 | F | 0 | 40 | 3 | A | 1 |
55 | 29,606 | F | 0 | 34 | 4 | B | 1 |
56 | 24,352 | F | 0 | 35 | 1 | A | 1 |
57 | 47,180 | F | 0 | 45 | 5 | B | 1 |
58 | 49,033 | M | 1 | 54 | 10 | A | 1 |
59 | 53,174 | M | 1 | 47 | 10 | A | 1 |
60 | 53,429 | F | 0 | 45 | 7 | B | 1 |
61 | 53,627 | M | 1 | 47 | 10 | A | 1 |
62 | 26,491 | F | 0 | 46 | 7 | A | 1 |
63 | 42,961 | M | 1 | 36 | 3 | B | 1 |
64 | 53,174 | M | 1 | 45 | 5 | A | 1 |
65 | 37,292 | M | 1 | 46 | 0 | A | 1 |
66 | 37,292 | M | 1 | 47 | 1 | A | 1 |
67 | 41,188 | F | 0 | 34 | 3 | B | 1 |
68 | 57,242 | F | 0 | 45 | 7 | C | 0 |
69 | 53,429 | F | 0 | 44 | 6 | C | 0 |
70 | 53,174 | M | 1 | 50 | 10 | B | 1 |
71 | 44,138 | F | 0 | 38 | 2 | B | 1 |
Question A.
Examine the effect of training level on annual salary, controlling for age and experience factors. For this question, use 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.
Question B Examine the effect of both gender and training level on annual salary, controlling for age and experience factors. Use the same dummy variable for training as Question A. 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. Choosing between two regression equations (reported in Questions A and B) which one would you prefer to go with? Provide a brief interpretation of your decision based on your answers for question 1 of each of these problems
Step by Step Solution
There are 3 Steps involved in it
Step: 1
Get Instant Access to Expert-Tailored Solutions
See step-by-step solutions with expert insights and AI powered tools for academic success
Step: 2
Step: 3
Ace Your Homework with AI
Get the answers you need in no time with our AI-driven, step-by-step assistance
Get Started