Learn how to build, evaluate, and compare regression models for count data using SAS in this hands-on course. You'll begin by exploring datasets to determine their suitability for Poisson regression, then construct models using PROC GENMOD with the log link function and interpret key outputs.

As you progress, you'll evaluate model performance by identifying overdispersion, refining models, and applying statistical diagnostics to improve accuracy. The course then introduces negative binomial regression, helping you understand when it is more appropriate than Poisson regression, interpret the dispersion parameter, and compare models using criteria such as AIC and deviance. Through guided SAS implementations and practical examples, you'll develop the skills to analyze count data, justify model selection decisions, and evaluate model performance with confidence. This course is designed for learners seeking practical experience with statistical modeling in SAS and for those who want to strengthen their ability to select and assess regression models for count data. By the end of the course, you'll be able to implement, compare, and critique Poisson and negative binomial regression models using SAS to support informed analytical decisions.