Applied Statistics II. 3 credits

Catalog description

Overview of statistical principles of modeling. Topics include methods for analyzing data based on generalized linear models and diagnostic methods for assessing the assumptions of such models. Methods covered include linear models and analysis of variance for multifactor experiments with balanced and unbalanced data, linear mixed models, logistic and Poisson regression, and hierarchical log linear models for contingency tables. Offered by Statistics . May not be repeated for credit.