서울대학교 상산수리과학관 강당(129동 101호) 

Zoom 회의실 445 008 9509

 

Causation is a fundamental goal of research in various fields, yet classical statistical frameworks can only explain associations between variables. However, in the past 30 years, significant developments have emerged to better understand causal relationships. This talk will introduce basic concepts of causal inference, including potential outcome framework, randomization inference, propensity score, weighting, matching, and sensitivity analysis, with the goal of promoting counterfactual reasoning and experience with causal inference methods.