This course builds explicitly on the foundation that was laid in POLSCI 701. In that class, you learned the nuts and bolts behind statistical inference. In this course, we extend those tools to cover the linear model.

The linear model is the workhorse of political science research. Nearly all of the techniques you see in published Political Science journals are either direct extensions or close relatives of the linear model. It is a very powerful tool for understanding relationships among a wide variety of types of variables.

The course will teach you the ins and outs of estimation, interpretation, diagnostics and presentation of the linear model. If time permits, we will move on to models for binary dependent variables, but I suspect there will be little time for that.

**Syllabus****pdf**

## Course Materials by Class Meeting

*1* Course Intro

- Slides
**pdf**

*2* What is Regression?/Examining Data

*3* Intro to Linear Regression

*4-5* Inference for Linear Regression

*6* Factor Explanatory Variables

*5* Interactions

*6* Linearity

*7* Linearity Lab

- Code
*R*