[AIRG] Causal inference in statistics 3/8

[Tim Huegerich <thuegerich@xxxxxxxxxxxx>]

AIRGers,

On Wednesday, March 13, at 4pm,

in CS 3310,
Tim Huegerich presents:
"Causal inference inÂstatistics: An overview"ÂÂ
by Judea Pearl
Statistics Surveys 3, 2009ÂÂ

http://dx.doi.org/10.1214/09-SS057ÂÂ

(Let me know if you have any access trouble.)

I will be presenting an introduction to causalÂinference in statistics,Â

especially as it pertains to observational dataÂand not randomizedÂ

controlled experiments. Causality in observationalÂdata is quiteÂ

important (because experiments are not always feasible orÂethical),ÂÂ
and it applies to many fields including economics and medicine.

The paper is long and I don't expect you to read all of it. (And itÂ
would be impossible to cover any substantial portion in a single AIRGÂ
session.) Here is what I suggest you read, in order of priority:

1. Abstract and Sections 1-2 (5.5 pages) for context.
2. As much of Section 3 as you can, but mainly up through Section 3.3.2Â
(~15 pages). This is the core technical material and where I will focusÂ
my presentation.
3. Introduction to Section 4 (0.5 pages). Explanation of the classicÂ
potential outcome framework.
4. Any more is further study for you and I do not plan to cover it.

See you next week.

Tim

p.s. Aubrey presented this same paper back in 2014, and credit for the summary above goes to him--I have copied the summary he used almost verbatim.