Advanced Regression Methods

3 Credits · Level: Undergraduate

This course expands on the concepts learned in Math-2540 and introduces students to advanced regression methods. We will start with a review of linear regression models, including model building and model diagnostics. The course will focus on generalized linear models (GLM) for non-Gaussian response data, including models for categorical outcomes (logistic, multinomial logit, proportional odds models) and models for count data (Poisson, negative binomial, zero-inflated models). If time permits, other advanced topics chosen by the instructor will be discussed. Statistical concepts will be accompanied by hands-on data analysis using the R statistical software.