Analysis of Truman State Retention Using Logistic Regression
Daniel W. Gladish
Dr. Hyun-Joo Kim, Faculty Mentor
Logistic regression is a statistical tool used to determine a relationship between a set of independent random variables and a binary dependent variable. This talk will cover a brief overview of the development of logistic regression, including the necessity of logistic regression with a binary response variable, maximum likelihood estimation of parameters, and hypothesis test to determine which independent variables are beneficial for the model. This technique is then applied to an analysis of the retention rate of Truman State. The data is obtained from the College Student Experiences Questionaire (CSEQ) and the Corporate Institutional Research Program (CIRP) surveys that students complete at Truman.
Keywords: Regression, Retention, Logistic , Statistics
Topic(s):Mathematics
Presentation Type: Oral Paper
Session: 21-4
Location: VH 1232
Time: 10:45