This course provides students with an overview of the literature on voluntary and involuntary migration throughout the world. Students are exposed to a variety of topics, including public attitudes toward migration, migrant experiences in host countries, and reasons for migration. The course is broken into two main parts. Part I discusses migration in the “Global North” and addresses concepts related to these migration patterns. Part II includes readings on migration in the “Global South.” In both parts, the goal is to help students develop an understanding of migration patterns, how host communities react to incoming refugees and migrants, and how the origins of migrants can affect these experiences. You can find the syllabus for this course here.

This course is the second in a sequence of three courses designed for the methods sequence of the Political Science PhD program at Ohio State. It covers the theoretical and applied aspects of linear regression and maximum likelihood estimation, with an emphasis on learning how to interpret and evaluate these models for both inferential and predictive purposes

My responsibilities in this course included designing weekly recitation sessions and assisting students with their weekly problem sets and understanding of the material, aside from general TA duties such as grading.

The R code used for recitation sessions can be found in the R Tutorials section.

This course was the first in a sequence of three courses designed for the methods sequence of the Political Science PhD program. It covers fundamentals of statistics and probability theory such as probability distributions, hypothesis testing, and basic linear regression.

This course focused on studying empirical and theoretical political science literature around social, political, and economic development. Students discussed various approaches to understanding development economics and the role that political actors play in these processes.