Question

The file 350_Case_2.xlsx contains starting salaries for 40 MBA students directly after graduation. These students were randomly selected from different universities. For each student, the file also lists the number of years of experience prior to entering the MBA program and their overall GPA in the MBA program. Besides, the file contains the overall ranking of the college/school on a 100-point scale (1=lowest, 100=highest). Use Microsoft Excel to answer all the questions below. Questions: 1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable. (5 + 5 = 10 points) 2. Present the simple linear regression equation, identify and explain the coefficient of determination, intercept and regression coefficient, and significance of F-test. Based on this analysis, is your regression equation “good for use”? Explain. (2 + 2 + 2 + 2 + 2 = 10 points) 3. Provide a numeric example of how this regression equation can be used to predict students’ starting salaries. (5 points) 4. Develop a multiple regression equation for starting salaries using School_Ranking, GPA, and Experience as independent variables. Is this regression equation “good for use”? Explain. (7 + 3 = 10 points) 5. If the multiple regression equation in the previous question is not “good for use”, how would you suggest improving this multiple regression equation? Present the improved multiple regression equation. Give a numeric example of how this improved multiple regression equation may be used to predict students’ starting salaries. (5 + 5 + 5 = 15 point

The file 350_Case_2.xlsx contains starting salaries for 40 MBA students directly after
graduation. These students were randomly selected from different universities. For each student,
the file also lists the number of years of experience prior to entering the MBA program and their
overall GPA in the MBA program. Besides, the file contains the overall ranking of the
college/school on a 100-point scale (1=lowest, 100=highest).
Use Microsoft Excel to answer all the questions below.

Questions:
1. Develop a simple linear regression equation for starting salaries using an independent
variable that has the closest relationship with the salaries. Explain how you chose this
variable. (5 + 5 = 10 points)
2. Present the simple linear regression equation, identify and explain the coefficient of
determination, intercept and regression coefficient, and significance of F-test. Based on this
analysis, is your regression equation “good for use”? Explain. (2 + 2 + 2 + 2 + 2 = 10 points)
3. Provide a numeric example of how this regression equation can be used to predict students’
starting salaries. (5 points)
4. Develop a multiple regression equation for starting salaries using School_Ranking, GPA, and
Experience as independent variables. Is this regression equation “good for use”? Explain.
(7 + 3 = 10 points)
5. If the multiple regression equation in the previous question is not “good for use”, how would
you suggest improving this multiple regression equation? Present the improved multiple
regression equation. Give a numeric example of how this improved multiple regression
equation may be used to predict students’ starting salaries. (5 + 5 + 5 = 15 point

Added by Muzhgan A.

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