This is a class about advanced quantitative analysis strategies used in political science. Quantitative data analysis refers to using statistical tools to analyze large data sets. This class is focused on applying the methods, but does not dive into the statistics of why the methods work, so this class is suitable for students with a limited math background. The first half of class focuses on regression models beyond the linear model covered in POL 3085. These models are used when your dependent variable is not continuous: for instance, dichotomous (0 or 1) dependent variables, ordered categories, unordered categories, or counts. The second half of class focuses on how text is used as data. We will cover cleaning and processing text data, describing and visualizing text data, sentiment analysis and other dictionary approaches, and topic modeling. Students are expected to have a basic knowledge of the R programming language.
Gopher Grades is maintained by Social Coding with data from Summer 2017 to Fall 2025 provided by the University in response to a public records request