o Employee Salaries provides data for 35 employees, including their age, whether they hold an MBA and the salary they receive.

o We would like to understand how their age and whether they hold an MBA affects their salary

Create a dummy variable to represent whether the employee has an MBA or not

Regression 1: Conduct a regression predicting salary with MBA and age.

Create an interaction variable MBA_Age_interaction by multiplying Age and MBA dummy variable.

Regression 2: Conduct a regression predicting salary with MBA, Age and MBA_Age_interaction

For both regressions, drop any variables that are insignificant and rerun regression if needed.

Which regression has a better fit? Provide evidence.

Using the regression with better fit,

- Which of the following statements would you agree with? Provide evidence.

a) Doing an MBA has no effect on salary

b) An MBA degree significantly increases salary from day 1

c) Those with MBA degrees have a higher increase in their salary with age

- Provide a point estimate for an 35 year employee with an MBA, and the associated 95% interval.

Employee	Salary	Age	MBA
1	28260	25	No
2	43392	28	Yes
3	56322	37	Yes
4	26086	23	No
5	36807	32	No
6	57119	57	No
7	48907	45	No
8	34301	32	No
9	31104	25	No
10	60054	57	No
11	41420	42	No
12	36508	25	Yes
13	40015	38	No
14	48329	47	No
15	39849	38	No
16	31985	31	No
17	59160	54	No
18	60335	59	No
19	35911	32	No
20	57814	55	No
21	42377	36	No
22	62430	60	No
23	46928	49	No
24	34403	35	No
25	45714	32	Yes
26	42247	27	Yes
27	54789	52	No
28	31702	30	No
29	34406	33	No
30	84876	57	Yes
31	27399	24	No
32	55785	51	No
33	34649	30	No
34	64236	61	No
35	50241	45	No