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by Anon84 1936 days ago
You might enjoy my blog series on Causality where I work through Pearls 'Causal Inference in Statistics: A Primer' using Python:

https://github.com/DataForScience/Causality

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2 comments

I have skimmed the first 2 chapters and I still don't understand how causal inference is a useful tool or how you apply it to anything moderately complex.

Obviously being able to identify causality is useful, but I don't understand how you can apply causal inference and get a meaningful result.

To apply any of the rules regarding DAG structure you first have to have a DAG of events, which seems like it would be difficult to accurately build up.

Wow what an amazing work. Thank you!
Thank you! The only way for me to learn anything is to work through it so this time around I decided to make my work public.

I’m glad you found it useful.