I teach graduate course on quantitative methods and political behavior.

Introduction to Political Communication

2020 Winter

This course explores the role of the media in politics with a particular focus on how mass and social media influence political attitudes, beliefs, and behaviors. The goal of the seminar is to (1) introduce students to key ideas about the role of media in democratic and non-democratic politics (2) engage with empirical research on the effect of of communication on individual behavior and (3) discuss the transformative changes that the media and its relationship with politics undergoes as a results of the internet and social media.

Frontiers of Political Research: Topics, Trends, Techniques (with Carsten Schneider)

2020 Winter

The course is an exploration of research frontiers in comparative politics that are opening due to both new social, political, and technological developments and changes in the way the discipline studies both old and new phenomena. New approaches that have emerged in the discipline include the use of novel data (e.g. due to digitization), tools of analysis (e.g. machine learning), and more careful thinking about cause and effects (e.g. a more design-based approach to inference and reflections on the mechanisms behind cause-effect relations). The course then consists of three parts. In the first part, we identify and discuss emerging standards of how to do empirical research in Political Science. The second part focuses on new strategies of generating data for political research. In part three, we assess how old topics are studied with these new standards and new data.

Applied statistics

2019 Fall

The goal of this class is to familiarize students with some of the core methods used by political scientists to make causal inferences using quantitative data. We will cover both experimental and observational methods that can be deployed to test theories and for each approach we will consider their strengths and limitations. During the first part, we will reconsider some of the key concepts of causal inference to provide a groundwork for assessing the methods discussed during the remainder of the course. Then, during each week of the course we will consider one method at a time – first discussing the underlying theory and assumptions and then discuss one or two applications (i.e. journal articles that utilize a particular method). By completing the class, students should acquire a basic understandings of the modern methods of causal inferences and develop an intuition about when and how these methods should be used.

Introduction to Statistics

2019 Fall

This is an introductory class in quantitative methods with the goal of (1) rigorously explaining some of the core concepts in statistics (2) giving an overview of some basic tools that can be used to learn from data and (3) apply these basic tools using statistical software. At a minimum, by the end of the course students should feel comfortable to both make and critically engage with arguments involving statistics. Moreover, the course will provide the foundations (aka prerequisites) for more advanced classes offered in the Department and elsewhere