Political Science 755 - Intro to Quantitative Analysis

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. Upon completion, students will be able to understand, evaluate and criticize the use of basic statistical methods for social science research. The course will also serve as a useful basis for more advanced research methods courses.

Open to POLISCI and DACSS graduate students. Students from outside the department can enroll with instructor permission.

For interested DACSS students: This course assumes a working knowledge of R. If you do not have a strong background in R (e.g., have not already taken and passed DACSS 601 Data Science Fundamentals or an equivalent), please contact the instructor to discuss strategies for preparing for this course.