A Statistical Analysis of GRE/GMAT Data for Admission to Master’s Degree Programs

Abstract

In this paper, we investigate the waiving of GRE/GMAT for admission to master’s degree programs in a state university in Florida, USA. Standardized tests, such as GRE/GMAT, were required for admission to the master’s degree programs in 2019/2020, waived in 2020/2021, and removed or modified in 2021/2022. We analyzed the application, enrollment, and performance data to assess the impact of these changes. The data show that the number of applicants and enrolled students exhibit an upward trend from 2019 to 2021. The undergraduate GPA of new applicants who did not submit the GRE in 2021 tends to be statistically significantly higher than for those who did submit the GRE in 2019 (p < 0.001). The new students’ first-semester graduate GPA in 2021 (no GRE requirement) tends also to be statistically significantly higher than the new students’ first-semester graduate GPA in 2019 (GRE requirement) (p< 0.01). The study employed random forest feature importance using the Gini index to analyze the predictive power of GRE and undergraduate GPA for forecasting first-semester graduate GPA. The results show that undergraduate GPA is a more significant factor than GRE. Overall, the study’s statistical evidence indicates that waiving GRE/GMAT requirements for master’s degree programs did not affect applicants’ performance, as measured by their undergraduate GPA, nor did it lead to a decline in student performance, as measured by first-semester graduate GPA.