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, create 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

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
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Author:Carter
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Chapter10: Statistics
Section10.1: Measures Of Center
Problem 8PPS
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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, create 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

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