This course introduces students to the most common quantitative empirical research design in political science and international relations: the linear model. The goal of the course is for students to understand when and how to apply the linear model to data, and to be able to do so appropriately. This means that we will learn about the underlying assumptions of the linear model, how most “social” data breaks these assumptions, and what we can do about that to still learn from our data using linear regression. The course does not involve intensive discussion of mathematics or probability theory, but will review these concepts to ensure students understand conceptually what linear regression is doing.

The course is focused on hands-on applications of linear regression and data processing to make data ready for analysis. Students will spend a significant portion of class time coding using the R software package, but no coding experience is expected or required.