Applied Regression Analysis

Catalog description

Emphasis Track(s) suggested for: Population Science, Health Systems Science Prerequisites: 19225 Introduction to Statistical Analysis. This course will provide an introduction to the foundations and principles of regression through hands-on training in advanced regression techniques using statistical software. Statistical analyses covered will include multiple linear regression, analysis of variance, logistic, ordinal logistic regression, and mixed models. Students will become acquainted with the basics of coding and interpreting results of regression analyses, as well as diagnostics to confirm correct model fit. By the end of the course students will be able to conduct regression analyses independently and interpret results. Coursework will include weekly reading, in-class analyses, and completion of a focused course project developed throughout the semester. Course projects will allow students to develop their skill set independently coding in statistical software to complete analyses and interpreting results within the context of strengths and limitations of each test. The final project will also incorporate both literature review and developing a research question that can be analyzed using existing data.