Using multiple linear regression and factor analysis to explore the determinants of students success at the university

Abstract EN

This paper studies the determinants of university success using a data set collected from a random sample from a Palestinian university.

we used multivariate inferential data analysis techniques like factor analysis and multiple linear regression to model the relationship between the variables and compare these models across faculty groups and student seniority at school.

the results show that high school grades are strongly associated with university success.

the results also show that the next important predictors of university success are “having scholarships”, English language proficiency, and class attendance, whereas variables measuring psychological well-being, gender, type of residency, and smoking behavior have only a smaller impact.

moreover, the link between most of these predictor variables and university success is shown to vary substantially across faculties and across the student’s seniority level.

in some fields of study, some variables are significantly correlated with university success, while in other areas, these same variables are not.