Analytic Methods in Sports

Used to teach an introductory course on statistics to undergraduate students using sports examples. Its practical focus on application rather than theory ensures students develop immediately applicable skills for the rapidly expanding field of sports analytics.

Thomas A. Severini is a Professor of Statistics and Data Science at Northwestern University and a fellow of the American Statistical Association and the Institute of Mathematical Statistics. He earned his PhD in Statistics from the University of Chicago.

1. Introduction. 2. Describing and Summarizing Sports Data. 3. Probability. 4. Statistical Methods. 5. Using Correlation to Detect Statistical Relationships. 6. Modeling Relationships Using Linear Regression. 7. Regression Models with Several Predictor Variables. 8. Further Topics in Regression Analysis. 9. Some Advanced Methods. 10. Applying Analytic Methods to Daily Fantasy Sports.