Predicting Academic Performance of MBA Program Applicants
Series: . 2 ; 11Publication details: 2018-07-19Description: 42Subject(s): In: The Great Lakes HeraldSummary: "We report on an approach for aiding and strengthening the MBA Admissions process that was used at the Stanford University Graduate School of Business. Multiple regression models were used to make predictions of the academic performance of an applicant, if admitted to the MBA program. The present paper focuses on the prediction of academic performance. We discuss in detail the development of criterion variables, the secification of predictor variables, and the development estimation and validation of models to predict academic performance as well as issues associated with the implementation of the approach."| Item type | Current library | Status | Barcode | |
|---|---|---|---|---|
| Article | St. Francis Institute of Management and Research | Available | AR0736 |
"We report on an approach for aiding and strengthening the MBA Admissions process that was used at the Stanford University Graduate School of Business. Multiple regression models were used to make predictions of the academic performance of an applicant, if admitted to the MBA program. The present paper focuses on the prediction of academic performance. We discuss in detail the development of criterion variables, the secification of predictor variables, and the development estimation and validation of models to predict academic performance as well as issues associated with the implementation of the approach."
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