MATH 455 - Intro to Regression Models

Credits: 4

This course covers mathematical foundation and practical implementations of linear and generalized linear regression models. Topics include estimation and diagnostics of linear model, transformations of variables, model selection, polynomial regression and logistic regression. The emphasis of the course will be on applications. The materials will partially cover the syllabus of SOA Exam Statistics for Risk Modeling and that of Exam Predictive Analytics. Prerequisites:C or better in MATH 329 and MATH 448, or consent of instructor. Offered regularly.