PS405 Linear Models

Winter 2025, Instructor

Graduate

This course is about linear models, the major workhorses of statistics for description and prediction, and one of the most common quantitative methods in political science. We will use a linear models framework to discuss significance tests, graphical displays, tests of assumptions, interpretation of coefficients and interactions, and questions of causal inference. We will also work through statistical computing skills such that students can use all of the above in their own work.

In this course we will build from probability theory to understand how linear regression produces estimates of conditional expectations. By the end of the course, students will be able to use R statistical software to estimate linear regressions and extensions upon the linear model, characterize the uncertainty of those estimates, conduct tests, and present results. Students will be able to interpret the results and discuss their relevance to political science research.