This course continues the graduate sequence in quantitative methodology for the social sciences. The methods will primarily apply to political science, but are useful for research in other social sciences such as economics, sociology, and psychology. The focus of this class is to conceptually understand the use of regression models for statistical inference, properly apply these methods to analyze data using statistical software, draw valid conclusions, and present these conclusions in a concise and clear manner.
Quantitative social science is difficult. Unlike the ‘hard’ sciences, we rarely have the opportunity to run experiments in controlled lab settings. We will be methodologically pluralist in our pursuit of accurate answers to important research questions.
We will learn about statistics and causal inference. Mostly in lab, we will also learn about computation: how to summarize data from the real world. We will use the free programs R and RStudio. Course assignments include problem sets, a take-home midterm, a take-home final, and a short data analysis project.
Social science methods are often best learned during the research process. In this course, we will not only learn concepts; we will learn how to learn methods on our own—how to ask about and Google for methods information.