Courses Taught

As instructor (Vanderbilt)

  • Political Science Honors Seminar. (undergraduate - thesis capstone course)

  • The Politics of Autocracy. (undergraduate)

  • Comparative Authoritarianism. (graduate)

  • Understanding Policy Data: Analysis and Interpretation. (undergraduate)

As instructor (Columbia)

  • Math Refresher Course for Incoming PhD students. (graduate)

As teaching assistant (Columbia)

  • Experimental Research: Design, Analysis, and Interpretation. (graduate)

  • Principles of Quantitative Political Research. (undergraduate/graduate)

  • Comparative Democratic Politics // Data Analysis and Statistics for Political Science Research. (undergraduate)

Other instruction

  • Academic Expert, Impact Evaluation Clinic. (USAID, 2015 and 2016)
    Workshop covering topics in research design for USAID Democracy, Human Rights, and Governance program implementers.

Course Materials

I teach or have taught several classes on research design and quantitative methods. In these courses, I seek to make an understanding of research methodology accessible to students with and without a strong quantitative background. To facilitate this, I develop interactive apps using R Shiny to illustrate statistical concepts and communicate the relevant intuition. Below are some examples, developed jointly with Thao-Nguyen Ha. These are free for instructional use, but please include citations:

  • Central Limit Theorem. Illustrates the principles of the central limit theorem and implications of sample size through simulation.

  • Hypothesis Testing. Illustrates the intuition behind hypothesis testing and the substantive interpretation of a z-score and corresponding one- or two-tailed p-value

  • Statistical Significance. Allows user to explore the significance of design-based factors (sample size), data features (effect size), and analytic decisions (type of hypothesis test and critical threshold used) in determining statistical significance. Also illustrates the concept of Type I and II errors.