Statistical Models for Predicting College Success

Authors

Yelen NunezFollow

Document Type

Thesis

Degree

Master of Science (MS)

Major/Program

Statistics

First Advisor's Name

Sneh Gulati

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

George O’Brien

Third Advisor's Name

B.M. Golam Kibria

Keywords

Statistical Models, academic success

Date of Defense

11-13-2013

Abstract

Colleges base their admission decisions on a number of factors to determine which applicants have the potential to succeed. This study utilized data for students that graduated from Florida International University between 2006 and 2012. Two models were developed (one using SAT as the principal explanatory variable and the other using ACT as the principal explanatory variable) to predict college success, measured using the student’s college grade point average at graduation. Some of the other factors that were used to make these predictions were high school performance, socioeconomic status, major, gender, and ethnicity. The model using ACT had a higher R^2 but the model using SAT had a lower mean square error. African Americans had a significantly lower college grade point average than graduates of other ethnicities. Females had a significantly higher college grade point average than males.

Identifier

FI13121216

Recommended Citation

Nunez, Yelen, "Statistical Models for Predicting College Success" (2013). FIU Electronic Theses and Dissertations. 1036.
https://digitalcommons.fiu.edu/etd/1036