Topics in causal inference

Speaker:Peng Ding (University of California, Berkeley)
Schedule:Mon.& Wed., 19:20–20:55, June 5-July 24, 2023; 18:00-21:00, July 26, 2023 (updated)
Venue:(Only on-site) Lecture Hall, Floor 3, Jin Chun Yuan West Bldg.
Date:2023-06-05~2023-07-26

Description:

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


Prerequisite:

Calculus, linear algebra, probability, statistics


Reference:

Lecture notes from the instructor

A First Course in Causal Inference.pdf


Target Audience: 

Undergraduate students & Graduate students


Teaching Language: 

Chinese


Bio:

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.  



Registration:https://www.wjx.top/vm/riDZtV7.aspx# 

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


Notes:

Note Jun 5, 2023.pdf

Note Jun 7, 2023.pdf

Note Jun 12, 2023.pdf 

Note Jun 14, 2023.pdf

Note Jun 19, 2023.pdf

Note Jun 21, 2023.pdf

Note Jun 26, 2023.pdf

Note Jun 28, 2023.pdf

Note Jul 3, 2023.pdf

Note Jul 5, 2023.pdf

Note Jul 10, 2023.pdf

主分层july 12 and 17.pdf

Note+Jul+19,+2023.pdf

Note+Jul+24,+2023.pdf

Note+Jul+26,+2023.pdf