17.803 LAB: Political Science Laboratory (with Stuart Russell)

This course introduces undergraduates to quantitative research in political science. Over the course of the semester, we explore themes in statistical research with an emphasis on causal inference. Through a combination of problem sets and a final project, students become familiar with the quantitative political scientist's tool kit and build competence in programming in R. 

17.THT: Political Science Thesis Seminar

17.THT is the 12-unit subject for students who elect to write a senior thesis under the supervision of a faculty member in the Department of Political Science. During this semester, students will develop their research topics, review relevant research and scholarship, frame their research questions and arguments, choose an appropriate methodology for analysis, draft the literature review and methodology sections of their theses, and write and present a thesis prospectus. 



17.800: Quantitative Research Methods I: Regression

This is the first course in MIT's sequence on quantitative political methodology for PhD students. 17.800 ("Quant 1") provides an introduction to regression models, along with the basic principles of probability and statistics which are essential for understanding how regression works. During the semester, students are introduced to the fundamentals of probability, point estimation, and linear regression models. Students are expected to understand the probability and mathematical principles behind point estimation and regression, building on skills they developing during MIT's Math Camp.

Through a series of problem sets and quizzes, students develop proficiency in the fundamentals of quantitative political methodology, learning the mechanics of regression modeling and developing both analytical and computational skills. Students also develop proficiency in R.


Introduction to Research Design. 

This workshop was aimed at introducing undergraduate research assistants to research design. The workshop focused on different research goals (for example, descriptive versus causal inference), and the types of tools available for such goals. Topics covered included descriptive statistics, randomized experiments, difference-in-difference designs, and matching. The workshop presentation can be found here

Fielding Online Experiments. 

This workshop is part of MIT's Political Methodology Lab workshop series. These workshops are intended to give participants a hands-on introduction to issues in quantitative methodology, including using SQL databases, Tidyverse, and GIS in R. In this particular workshop, I cover issues related to fielding online experiments. Topics covered included selecting an online sample pool, programming online experiments with Qualtrics and mTurk, and common data quality issues. The workshop presentation can be found here