BAN 510 - Sports Analytics

Course Description: This course explores computer-intensive methods for model selection, parameter estimation, and validation for predictive analytics. The course focuses on techniques and algorithms from the statistical and machine learning disciplines and has a strong programming component. Example topics in this course include ordinary least squares regression, logistic regression, multinomial logistic regression, classification and regression trees, neural networks, support vector machines, naïve Bayes, principal components analysis, cluster analysis, and regularization. Each technique is accompanied with a focus on application and problem-solving.

Credit Hours: 3

Course Repeatability: Course may not be repeated

ADDITIONAL COURSE INFORMATION

Click here for the Spring 2025 Class Schedule.