alt Hacker NewsMy personal opinion is that statistics textbooks usually come from a prescriptive perspective, and that makes it challenging for the reader to get visceral intuition for what is actually going on. Any reader would be far better off just visualizing the damn distribution / samples and using reasonable judgement, instead of implicitly assuming a Gaussians distribution and blindly memorizing tests / formulae. Making the distributions explicit allows us to model them and get an intuition for what the samples are telling us. I would whole-heartedly recommend the Model based machine learning book to anyone (online version is free) https://mbmlbook.com/
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My larger issue, any time I have tried to learn statistics, is how fast the notation moves. You end up flipping back pages and pages just to double-check a definition that was given once and is now being extended syntactically. It's infuriating.
How do you make 'reasonable judgements'? How do you tell whether someone else made reasonable judgements? How do you judge other people's intuition?
Modelling distributions explicitly sounds nice, yes.