Files
Download Full Text (863 KB)
Description
Gretchen Mann, Applied Mathematics
Faculty Mentor: Professor Bruce Swan, Mathematics
Within the past couple of decades, attending any one of the eight Ivy League schools has been increasingly more competitive and the admission rates have been declining year after year. This is primarily due to more prospective students applying than in previous decades. While the average number of students that an Ivy League school accepts in any given year is approximately consistent, the average number of applications received has been trending positively. As a result, the average admission rates for Ivy League schools have been gradually declining since 2003. By using SPSS and creating a multivariate time-series regression model, my project forecasts the average number of Ivy League school applicants for the 2020-2021 academic year. Other potential time-dependent variables will be introduced too, such as the total number of high school graduates, SAT and ACT scores, average grade point average (GPA), mean parental income, average financial aid package awarded, and average indebtedness after graduation. Potential models were created based on these predictors, using stepwise regression methods such as forward selection and backward elimination. The ultimate goal of this paper is aimed towards choosing and analyzing a best-fit model, based on the criteria of how significant it is at predicting the average number of applicants and how the optimal model fits compared to other potential models. Multicollinearity between the regressor variables was also analyzed in the models.
Publication Date
2020
Disciplines
Physical Sciences and Mathematics
Recommended Citation
Mann, Gretchen, "The Models for the Average Number of Applicants at Ivy League Schools" (2020). Mathematics. 22nd Annual Student Research and Creativity Conference. SUNY Buffalo State.
https://digitalcommons.buffalostate.edu/srcc-sp20-math/2
