aaryanMontana / notes-on-causal-inference

Some notes on Causal Inference, with examples in python

Notes on Causal Inference

When learning about new things, I find it helps to write explicit notes on what I am trying to understand. These are my note for trying to understand "Causal Inference", or how we can make questions like "What effect does changing $X$ have on $Y$?" precise. I am not an expert on the subject, for a popular account from an expert I suggest Pearl's The Book of Why: The New Science of Cause and Effect. For a more mathematical account, I suggest Elements of Causal Inference.

These notebooks are for the following blog posts:

• http://www.degeneratestate.org/posts/2018/Mar/24/causal-inference-with-python-part-1-potential-outcomes/
• http://www.degeneratestate.org/posts/2018/Jul/10/causal-inference-with-python-part-2-causal-graphical-models/
• http://www.degeneratestate.org/posts/2018/Sep/03/causal-inference-with-python-part-3-frontdoor-adjustment/

References

• http://laurence-wong.com/software/
• https://cs.nyu.edu/~shalit/slides.pdf
• https://mitpress.mit.edu/books/elements-causal-inference
• https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/
• https://github.com/ijmbarr/causalgraphicalmodels