Causal inference for statistics, social and biomedical sciences
任课教师 Speaker：Donald Rubin & Per Johansson
时间 Time： 每周二 19:20-21:45 2021-9-13 ~ 12-31
The course will teach causal inference for causal effects using the concept of potential outcomes; here a causal effect is defined as the comparison between two values of an outcome variable, either of which can be observed but not simultaneously. Which one is actually observed can be decided by the toss of a coin, as in a randomized experiment, or generalizations of a coin toss, as in observational studies. This perspective is sometimes called the “Rubin Causal Model”.
Zoom Meeting ID：849 963 1368