Linear Models (405-0-20)

Instructors

Jaye Seawright
847/467-1148
Office Hours: http://www.polisci.northwestern.edu/people/core-faculty/jason-seawright.html

Meeting Info

Scott Hall 212: Mon, Wed 11:00AM - 12:20PM

Overview of class

This course is about linear models (regression), which involve a set of techniques that show up across nearly all areas of statistics. Regression models are used as a powerful tool to describe data, have value for forecasting, and are sometimes pressed into service for work in theory-testing and causal inference. Across these use cases, linear models are everywhere in political science.

We will talk about regression as a tool for data summary; discuss ideas about generalization and significance tests in the context of these models; develop skills with common graphical displays; clarify key assumptions and explore available tests of assumptions; practice interpreting the results of regressions; and discuss when/if regression can speak to causal questions. In each of these areas, we will connect our quest for understanding with hands-on statistical computing work.

Registration Requirements

Recommended: Political Science 403 or equivalent

Learning Objectives

Students will understand and be able to explain the core math of how linear regression produces estimates. Students will be able to use R statistical software to estimate linear regressions and related techniques, and will be able to clearly and correctly explain the results. Students will be able to explain the various measures of uncertainty reported in conjunction with regression estimates, and choose one or more measures to best characterize a given set of results. They will be able to conduct and interpret significance tests involving regression and related models. Students will be able to develop graphs and tables suitable for professional academic use in communicating statistical results. Finally, students will be able to explain what regression results teach us about political science questions.

Teaching Method

Lecture and discussion/lab

Evaluation Method

Problem sets, quizzes, final project

Enrollment Requirements

Enrollment Requirements: Reserved for Graduate Students.