OCAIR Best Presentation Award Topic–Study on Factors that May Impact the Enrollment Results of Admitted Applicants
Yangzi Mao, Minghui Wang and Faxian Yang
Abstract:
This study predicts admitted applicants’ likelihood to enroll based on several key characteristics, including variables from demographic, preparedness, time-related, and financial categories. K-State’s applicant data from 2016 to 2021 were used. Bivariate analysis between enrollment results and each variable was conducted. Several predictive models were built and then compared. And a logistic regression model was used to identify each factor’s effects on enrollment probability.
.
You must be logged in to post a comment.