Intermediate Quantitative Methods for Politics

(4 Credits)

The course prepares students to (1) conduct original quantitative political science research in preparation for thesis, seminar, or honors projects in subsequent semesters and to (2) take higher-level data analysis courses such as causal inference or courses in data science. Topics include reproducible statistical programming, data visualization, univariate and multivariate data analysis, regression, addressing confounding, and sample-theoretic statistical inference. The course is hands-on and involves frequent quantitative inference and statistical programming activities both in class and as homework assignments. Assignments will require that students demonstrate both conceptual/mathematical understanding and the ability to conduct reproducible data analyses.