2. In an attached Excel file, there is data taken from Forbes magazine’s website. It shows data for the top 20 business schools in the country. Use the data and run the following three regressions:

 GMAT score as a predictor of post MBA salary

 Tuition as a predictor of post MBA salary

 Both GMAT score and tuition as predictors of post MBA salary

For each regression that you run, discuss the goodness of fit based on:

 R 2

 P values

 Confidence intervals

 Residual plots

Answer the following questions based on the regression output that you obtain:

 Which regression model is the better predictor of post MBA salary? How do you know?

 Does multicollinearity appear to be a problem in the multiple regression? Why or why not?

 Predict post MBA salary for someone who scores a 710 on the GMAT.

 If GMAT score increases 10 points, how will post MBA salary change?

 Predict post MBA salary for someone who paid tuition of $50,000.

 If tuition decreases $5000, how is post MBA salary expected to change?

 Predict post MBA salary for a person that earned a 680 on the GMAT and paid tuition of 60 (thousand)

 Student A earned 25 points more than Student B on the GMAT. How much greater is Student A’s post MBA salary?

 Students A and B both paid tuition of 70 (thousand). Student A earned 50 points less on the GMAT than Student B. What is the difference in Student A’s post MBA salary as compared to Student B?

Price: $16.03

Solution: The downloadable solution consists of 8 pages, 803 words and 4 charts.
Deliverable: Word Document