My teaching interests include American politics, state and local politics, public policy, elections, and political parties, along with undergraduate and introductory graduate courses in formal and quantitative methods. I have served as preceptor (assistant instructor) for three different courses at Princeton:
Quantitative Analysis (Advanced), Fall 2015 (taught by Mark Watson), Masters Level
Statistical analysis with applications to public policy. The course begins with an Introduction to probability theory followed by discussion of statistical methods for estimating the quantitative effects of changes in policy variables. Regression methods appropriate for the analysis of observational data and data from randomized controlled experiments are stressed. The basic level (507B) assumes a fluency in high school algebra and some familiarity with calculus, while the advanced level (507C) assumes a fluency in calculus.
Quantitative Analysis and Politics, Fall 2014 (taught by Marc Ratkovic)
Which countries are more likely to erupt in civil conflict? Does government aid increase support for incumbent politicians? Who is more likely to win the next election? Assessing questions like these, and others beyond political science, requires an understanding of statistical inference. This course provides the foundation necessary to conduct statistical analyses in the social sciences. The course will focus on statistical concepts, including probability, causality, estimation, and inference. Combining programming, statistical theory, and real world datasets, this course will introduce students to the basic principles of data analysis.
Introduction to American Politics, Fall 2013 and Spring 2016 (taught by Nolan McCarty)
A survey of the institutions of American democracy. Topics will include the Constitutional order, federalism, legislative deliberation, executive power, elections and representation, interest groups and social movements, the courts, and policymaking.