OCAIR Best Presentation Award Topic–Study on Factors that May Impact the Enrollment Results of Admitted Applicants
Yangzi Mao, Minghui Wang and Faxian Yang
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.