COMM382 - Big Data and Causal Inference

Massive datasets are increasingly available for research as digital technologies pervade our lives. These data represent new opportunities for social science research, but prominent examples of data science research bear little resemblance to the research designs of social scientific inquiry. In this course, we use machine learning and statistical tools on large-scale datasets to answer social science questions of cause and effect. Familiarity with Python recommended. Enrollment limited to PhD students in COMM or Social Science who have completed or are currently taking graduate quantitative methods sequences in Economics, Political Science, Sociology, or Statistics. Contact ohtammy@stanford.edu for a permission number to enroll (please include a current CV).
Career
Graduate
Grading Basis
ROP - Letter or Credit/No Credit
Min
1
Max
5
Course Repeatable for Degree Credit?
No

Course Component
Seminar
Enrollment Optional?
No