Topics in causal inference

Speaker:Peng Ding (University of California, Berkeley)
Schedule:Mon.& Wed., 19:20–20:55, June 5-July 31, 2023
Venue:(Only on-site) Lecture Hall, Floor 3, Jin Chun Yuan West Bldg.


This course will cover the following basic topics:

- randomization inference in experiments: design and analysis

- observational studies: identification and estimation with and without unconfoundedness, sensitivity analysis

- causal mechanisms: post-treatment complications, interaction

- difference in differences and panel data

- spillover and peer effects


Calculus, linear algebra, probability, statistics


Lecture notes from the instructor

A First Course in Causal Inference.pdf

Target Audience: 

Undergraduate students & Graduate students

Teaching Language: 



Peng Ding is an Associate Professor in the Department of Statistics, UC Berkeley, working on causal inference. He obtained his Ph.D. from the Department of Statistics and worked as a postdoctoral researcher in the Department of Epidemiology, both at Harvard.  


[Deadline: 12:00 (noon), May 30, 2023]