Summary of Output Regression Statistics Questions

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 refer to this textbox: Prince, J. (2018). Predictive Analytics for Business Strategy. McGraw-Hill