Statistical Models for Predicting College Success Thesis

(2013). Statistical Models for Predicting College Success . 10.25148/etd.FI13121216

thesis or dissertation chair

authors

  • Nunez, Yelen

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.

publication date

  • November 13, 2013

keywords

  • Statistical Models
  • academic success

Digital Object Identifier (DOI)