When a player is a free agent, an individual who is able to sign to any team, one wonders what their best option is. Will signing with Team A or Team B provide them with the largest salary? What factors will affect their salary the most? Does last year’s statistics have a strong impact on next year’s salary? These questions can be answered by performing a regression analysis on previous years data. The primary focus of this project is to determine the most important variables related to an NBA salary. Likewise, the statistical programs SAS and R will be compared in their efficiency along with the importance of using two programs. Additionally, a comprehensive guideline of completing a regression analysis will be developed. Specifically, the use of a Box-Cox Transformation will be considered along with the use of t-Tests, a Breusch- Pagan test (constant variance), and many more statistical tests and methods.
Dr. Uma Shama, Thesis Advisor
Dr. Wanchunzi Yu, Thesis Advisor
Dr. Mahmoud El-Hashash, Committee Member
Copyright and Permissions
Original document was submitted as an Honors Program requirement. Copyright is held by the author.
Milligan, Sarah. (2021). Guidelines for Regression Analysis in SAS and R: A Case Study. In BSU Honors Program Theses and Projects. Item 572. Available at: https://vc.bridgew.edu/honors_proj/572
Copyright © 2021 Sarah Milligan