Using Regression to Establish Weights for a Set of Composite Equations through a Numerical Analysis Approach: A Case of Admission Criteria to a College

Abstract

Problem statement: Mathematically little is known of college admission criteria as in school grade point average, admission test scores or rank in class and weighting of the criteria into a composite equation. Approach: This study presented a method to obtain weights on “composite admission” equation. The method uses an iterative procedure to build a prediction equation for an optimal weighted admission composite score. The three-predictor variables, high school average, entrance exam scores and rank in class, were regressed on college Grade Point Average (GPA). The weights for the composite equation were determined through regression coefficients and numerical approach that correlate the composite score with college GPA. Results: A set of composite equations were determined with the weights on each criteria in a composite equation. Conclusion: This study detailed a substantiated algorithm and based on an optimal composite score, comes out with an original and unique structured composite score equation for admissions, which can be used by admission officers at colleges and universities.