Toni Sipic (Economics)
Universities are always looking for ways to streamline the enrollment process. The process of sorting all of the applicants, choosing which ones to accept, and then documenting all of those who choose to enroll can be an inefficient time-consuming process. This study aims to find significant determinants of enrollment of potential students after they have been accepted into the university. This study does not try to predict acceptance, it only focuses on the students who have already been accepted and are choosing whether to attend the university. The sample for this study is drawn from students who were accepted into Central Washington University within the last decade. The variables tested were the characteristics of the potential student regarding sex, first generation student, FAFSA, veteran, state resident, race, income bracket, SAT score, and high school GPA. A standard logit general linear model was used to run a regression on the data using the default log link function. The results of the regression did yield a significant relationship between some of the variables we tested. Sex, FAFSA, income, veteran, high school GPA, and SAT score all proved to be significant variables indicating a likelihood to enroll after acceptance. This proves that some preliminary action in the acceptance office could potentially increase the efficiency of the enrollment process at the university level.
Keywords: Regression Analysis, Education, Statistics