This course is designed to introduce students to the basic principles and concepts of regression analysis as applied to public health. This class will proceed systematically from the examination of the distributional qualities of the measures of interest, to assessing the appropriateness of the assumption of linearity, to issues related to variable inclusion, model fit, interpretation and regression diagnostics. Specifically, this course will introduce various statistical methodologies and regression modeling, including hypothesis tests, one-way ANOVA, correlation, linear regression, logistic regression, Poisson regression, survival analysis and Cox proportional hazards model. Additionally, the course provides hands-on training in analyzing public health data using SAS or R software.
Prerequisites: HSC 382 and HSC 383, each with a minimum grade of C.