This course is for SBS who want to learn to teach their peers to be successful in college. Students assist a primary instructor in the teaching of a First Year Seminar that meets weekly throughout the semester. In addition, some assignments will occasionally require working with the FY students outside of class. Students in this class meet weekly in their own seminar where they discuss issues around classroom management, teaching techniques, and organizational skills, such as working with Moodle or another LMS.

This course serves as a rigorous introduction to quantitative empirical research methods, primarily for doctoral students in political science (but also suitable for other social scientists). The material covered will include probability theory, distributions of random variables, data visualization, principles of statistical inference (estimation and uncertainty), covariate adjustment (a.k.a. linear regression), and a brief introduction to causal inference. Simulations and data analysis will be conducted in the R statistical environment or Stata.

This course introduces graduate students to the logical foundations of research methods and the wide variety of methodologies used by political scientists.

In this course, we will consider such questions as: What do we know and how do we know it? What knowledges count as science? How is knowledge culturally situated? How has science been central to colonialism and capitalism and what would it mean to decolonize science(s)? Is feminist science possible?