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I completely agree; I've found it much harder to self-learn the stats than the software side of things. Sibling post makes a good point, but I think the history of stats vs. comp sci bears weight here too; having many people want to learn stats outside academia is a much newer phenomenon than people doing the same with programming.

Anyone have any good resources for self-teaching stats? I have a BS in math but only took one stats course, and it was as terrible as all intro-stats classes are. I have a strong, proof-based understanding of probability theory, but haven't found a similar approach to stats. It all seems to be "if data looks like this, use this test, watch for these pitfalls" which is terrible for building intuition.



Try the Khan Academy stats resources - https://www.khanacademy.org/math/statistics-probability

Datacamp also launched a bunch of new stats courses recently. I haven't checked them out yet, but their courses are usually good quality. https://www.datacamp.com/courses/topic:probablity_and_statis...


If you like proofs and rigor, take a look at "Statistical Inference" by Casella and Berger.




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