Baseball Analytics: Data Science and Statistical Modeling with Baseball Data credit: 3 or

4 Hours

Statistical and data science techniques for baseball analytics, focusing on player evaluation, performance metrics, and modeling team wins. Emphasis is placed on data transformation, visualization, and predictive modeling. While baseball is the primary case study, the quantitative methods taught are broadly applicable to data science, business analytics, and performance evaluation across industries. A background in baseball is not required. 3 undergraduate hours. 4 graduate hours. Prerequisite: STAT 385 , STAT 425 , and STAT 410 .