Quantitative Analysis and Politics (TA, Princeton University)
What accounts for who votes and their choice of candidate? Would universal health insurance improve the health of the poor? Researchers and policy makers use statistics to answer these questions. However, the validity of their conclusions depends upon underlying assumptions and correct application of statistical methods. The course will introduce basic principles of statistical inference and programming skills for data analysis. The goal is to provide students with the foundation necessary to analyze data in their independent research at Princeton and to become a critical consumer of news articles and academic studies that use statistics. (Under Kosuke Imai.)

Visualizing Data (TA, Princeton University)
Equal parts art, programming, and statistical reasoning, data visualization is critical for anyone who seeks to analyze data. Data analysis skills have become essential for those pursuing careers in policy evaluation, business consulting, and research in fields like public health, social science, or education. This course introduces students to the powerful R programming language and the basics of creating data-analysis graphics in R. We use real datasets to explore topics ranging from networks (like trade between counties) to geographical data (like the spatial distribution of insurgent attacks in Afghanistan). (Under Kosuke Imai.)

Chinese Politics (
TA, Princeton University)
This course provides an overview of China's political system. We begin with a brief historical overview of China's political development from 1949 to the present. The remainder of the course will examine the key challenges facing the current generation of CCP leadership, focusing on prospects for democratization and political reform. Among other topics, we will examine: factionalism and political purges; corruption; avenues for political participation; village elections; public opinion; protest movements and dissidents; cooptation of the business class; and media and internet control. (Under Rory Truex.)

Course descriptions courtesy of the Princeton University Registrar.