The Certificate in Sports Statistics and Analytics will provide students with the knowledge and skills needed to work in the expanding field of sports analytics. Students will be able to acquire sports data using data scraping techniques and use these sports data to create graphical visualizations, generate summary statistics, build probabilistic models, assess hypothesis using statistical methods, create and evaluate regression models, implement machine learning algorithms, and present research findings in person and on paper.
Learning Objectives
Upon successful completion, students will be able to:
- Analyze the unique aspects of sports data and modeling sports data.
- Acquire sports data using data scraping techniques and R packages.
- Create graphical and visual summaries of sports data.
- Utilize theory and methods from probability, statistics, and machine learning to analyze sports data.
- Write summary and project reports related to unique sports datasets.
- Orally present research findings related to sports analytics to a general audience.
Effective Fall 2023
Additional coursework may be required due to prerequisites.
| Code | Title | Credits |
|---|---|---|
| STAT 351 | Sports Statistics and Analytics I | 3 |
| STAT 451 | Sports Statistics and Analytics II | 3 |
| Select one of the following: | 3 | |
| Intermediate Applied Statistical Methods | ||
| Statistical Computing | ||
| Introduction to Stochastic Processes | ||
| Bayesian Data Analysis | ||
| Applied Multivariate Analysis | ||
| Program Total Credits: | 9 | |