Explore the use of regression analysis in applied research and learn about multiple linear regression; ANOVA; logistic regression; random and mixed-effects models; and models for dependent data. Engage in the identification of appropriate statistical methods and interpretation of software output. R programming is introduced. Three lecture hours a week for one semester. Statistics and Data Sciences 324E and 332 may not both be counted. Prerequisite: Statistics and Data Sciences 302F and Statistics and Data Sciences 322E or Statistics and Data Sciences 320E.