Regression Model for Predicting Academic Success of Prospective Students in the AFIT (Air Force Institute of Technology) Graduate Logistics Management Program.

摘要

Counselors in the Admissions Division at the Air Force Institute of Technology currently determine academic eligibility of graduate programs candidates subjectively on the basis of criteria defining minimum acceptable undergraduate grade point averages (UGPA) and graduate admissions test scores. The determination could be made more uniformly and efficiently by a regression model that could predict each candidate's final graduate grade point average (GGPA) given his or her UPGA, test scores, and other background information. This study developed and validated such a model using data collected on 140 students of the Graduate Logistics Management (GLM) classes of 1986 through 1989. A regression model for predicting academic success fo prospective students in the AFIT graduate logistics management program. Mathematical prediction, Correlation techniques, Regression analysis, Personnel selection, Education. (eg)