The Utility of Discriminant Analysis for Predicting Graduation From a Master of Business Administration Program

Abstract

With universities facing enrollment ceilings and with increased competition for admission to graduate programs, it has become increasingly important for admissions committees to select those applicants who are most likely to complete their degrees. This study was concerned with the accuracy with which successful completion of the Master of Business Administration (MBA) degree could be predicted from readily available admissions data: sex of the student, student age, undergraduate grade point average, Graduate Management Admission Test (GMAT) Verbal score, and GMAT Quantitative score. As a mechanism for evaluating the predictive accuracy of the MBA admissions data, discriminant analysis was used. The sample for this study consisted of all students who had begun and in some way had concluded their MBA studies between 1969 and 1979. This total sample ( N = 507) was randomly split into two parts, one part for deriving the discriminant function and one part for cross-validating the derived discriminant function. The results of the dis criminant analysis clearly showed that the two criterion groups (graduates and non-graduates) could be differentiated. In addition, the utility of the discriminant function derived from the one sample was demonstrated on the cross-validation sample. Of the students in this hold-out sample, 69% of those predicted to graduate actually did.