Question 2 (12 points)

The "Job Search.xlsx" data set contains information on recent college graduates and their efforts

to find full-time employment.

Here is detailed information on the variables included in the data set:

Time to Find Job: The number of months it took students to find full-time employment

GPA: Calculated as usual on a 4-point scale with 4.0 being the highest possible

value

Effort in Job Search: A self-reported measure of how hard graduates tried to find full-time

employment. Possible values range from 1 ("Did not try very hard to find

a job.") to 5 ("Did everything I could to find a job as quickly as possible.")

Internship: Dummy variable which is coded as "1" if the student completed an

internship and "0" otherwise

Part (a) (2 points)

Open the "Job Search.xlsx" data set and run a multiple regression with "Time to Find Job" as

dependent variable on the following independent variables: "GPA," "Effort in Job Search," and

the "Internship" dummy.

You must submit your actual Excel file with the output as part of the assignment.

Part (b) (2 points)

Choose one of the three independent variables included in the regression and explain why we

expect that independent variable to have an impact on the dependent variable.

Part (c) (2 points)

Interpret the estimated value of the coefficient on the "GPA" variable, i.e., explain what the

number means in this regression.

Part (d) (2 points)

Interpret the estimated value of the coefficient on the "Internship" dummy variable, i.e., explain

what the number means in this regression.

Part (e) (2 points)

Is the estimate of the coefficient on the "GPA" variable statistically significant? Please answer

"yes" or "no," then explain how we can tell.

Part (f) (2 points)

Is the estimate of the coefficient on the "GPA" variable of practical significance? Please answer

"yes" or "no," then explain how we can tell.