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	53,908
2	32	78,230
3	14	55,164
4	20	57,647
5	25	63,111
6	14	54,991
7	28	74,571
8	30	73,189
9	28	71,859
10	17	55,978
11	14	61,676
12	6	44,865
13	21	64,676
14	11	59,101
15	14	58,441
16	32	81,964
17	29	76,373
18	33	82,860
19	27	70,019
20	16	58,474
21	26	80,074
22	3	45,594
23	14	63,676
24	9	68,444
25	14	70,306

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:

CustRate_i=+₁Inc_i+₂Age_i+₃Educ_i+₄Marr_i+U_i.

1. 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.
2. Test the hypothesis that 2=0.05, using a confidence level of 90%. Be sure to provide the reasoning behind your result.
3. Build a 95% confidence interval for the impact of education on customer rating. Be sure to provide the reasoning for your result.
4. Build a 95% confidence interval for the impact of being married on customer rating. Be sure to provide the reasoning for your result.
5. Predict the change in customer rating if a customers income increases by $10,000, with no change in age, education, or marital status.