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BAA 4 Employee Tenure and Salary Worksheet

Activity I - Your firm is interested in learning more about how its salaries relate to its employees’ tenure with the firm. It has collected the following data for 25 of its employees.

EMPLOYEE NUMBER

TENURE (YEARS)

SALARY ($)

1

15

53,408

2

32

77,230

3

14

53,664

4

20

55,647

5

25

60,611

6

14

51,991

7

28

71,071

8

30

69,189

9

28

67,359

10

17

50,978

11

14

56,176

12

6

38,865

13

21

58,176

14

11

52,101

15

14

50,941

16

32

73,964

17

29

67,873

18

33

73,860

19

27

60,519

20

16

48,474

21

26

69,574

22

3

34,594

23

14

52,176

24

9

56,444

25

14

57,806

Plot these data points, and describe using regression how salary relates to firm tenure for this group.

Activity II - The data attached contains information on customers’ ratings of your product (CustRate), on a scale of 1 to 100, along with demographic information. The demographic information includes: income (Inc), age (Age), education (Educ), and marital status (Marr). The last variable equals one if the respondent is married and zero otherwise. Assume the data-generating process can be written as:

CustRatei=α+β1Inci+β2Agei+β3Educi+β4Marri+Ui.

Test the hypothesis that income has no impact on customer rating, using a confidence level of 95%. Be sure to provide the reasoning behind your result.
Test the hypothesis that β2=0.05, using a confidence level of 90%. Be sure to provide the reasoning behind your result.
Build a 95% confidence interval for the impact of education on customer rating. Be sure to provide the reasoning for your result.
Build a 95% confidence interval for the impact of being married on customer rating. Be sure to provide the reasoning for your result.
Predict the change in customer rating if a customer’s income increases by $10,000, with no change in age, education, or marital status.
Please sure to use textbook
.Note: Please refer to this textbox: Prince, J. (2018). Predictive Analytics for Business Strategy. McGraw-Hill Education

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