Research on the Factors Determining the Chance of Graduate Admission


  • Yansong Li



Linear model; chances of admissions; application for master’s degrees.


Nowadays, due to various reasons, more students are beginning to pursue higher academic degrees, such as master's degrees. This article discusses the factors that influence the chances of graduate admissions. The aim is to quantify each determinant by establishing a linear model, thus helping everyone understand how much each factor can affect the admission chance. The dataset used in this article comes from the Kaggle, which includes eight variables and 400 observations. This article establishes several multiple linear models using the smallest AIC selection, the smallest BIC selection, and the LASSO selection. Models are screened based on some indicative values such as R2adj, SSres, and R2. After establishing the final model, assumptions (Normality, homoscedasticity, multicollinearity, linear relationship) and prediction errors are checked to verify the model's effectiveness. The article ultimately finds that every predictor positively correlates with the admission chances. It means that the more achievements an applicant has, the higher the chance of admission. This conclusion is consistent with our initial hypothesis. The final results can help applicants understand the importance of each application material (predictor). By inputting their existing achievements for each predictor into the model, they can predict their chances of admission, identify deficiencies, and work on improvements.


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How to Cite

Li, Y. (2024). Research on the Factors Determining the Chance of Graduate Admission. Highlights in Science, Engineering and Technology, 88, 1016-1023.