Advanced Regression and Nonlinear Models

Catalog description

Deepens understanding of how to analyze and interpret research data using techniques that build off a traditional multiple correlation/regression framework as frequently brought to bear to address questions posed by behavioral and social scientists. Enhances understanding of interaction terms (e.g., polynomial terms, moderation, among continuous and categorical predictors). Introduces generalized linear models for analyses specifying non-normal distributions such as logistic and Poisson regression, as well as maximum likelihood estimation and model-based reasoning perspectives to statistical inference.