Overview
Management : Design-based causal inference. Leveraging design choices, rather than statistical models, to establish causal effects in research. Causal inference in quantitative and qualitative research. Topics include the structure of theoretical arguments, measurement, causal graphs, sampling, and study design (e.g., quasi, natural, and field experiments and case studies).
Terms: Winter 2025
Instructors: Dakhlallah, Diana (Winter)
Prerequisites: introductory statistics course
Restrictions: Open only to Ph.D. students. Not open to students who have taken MGMT 710 when topic was "Designing Social Science Research for Causal Inference".
