The MBA program at a large university is facing a pleasant problem - too many applicants. The current admissions policy requires students to have completed at least three years of work experience and an undergraduate degree with a score of at least 75% on their MBA admission test. Up until three years ago, the school admitted any applicant who met these requirements. However, because the program recently converted from a two-year (four-semester) program to a one-year (three-semester) program, the number of applicants has increased substantially. The dean, who teaches statistics courses, wants to raise the admissions standards by developing a method that more accurately predicts how well an applicant will perform in the MBA program. She believes that the primary determinants of success are:

undergraduate grade point average (GPA)

MBA Admissions Test (MAT) score

number of years of work experience.

She randomly samples students who have completed the MBA and records their MBA program GPA, as well as the three variables listed above. These data are recorded and stored in the first four columns of the file MBA.wf1. Develop a model and test to decide which primary determinants should be used to select which applicants to admit. After considering the results of the initial study, the dean realised that she may have omitted an important variable - the type of undergraduate degree completed. She returned to her sample of students and recorded the type of undergraduate degree completed, using the following codes: 1 = BA; 2 = BCom; 3 = BEng or BSc; 4 = Other (including no undergraduate degree). These data are provided in the fifth column of the data file. Can the dean conclude that the type of undergraduate degree completed is a factor in determining how well a student will perform in the MBA program?

Please use Eviews software to explain the steps. Thanks!