Data:
{
"text": "That’s not bad to be fair. \n\nIf you check the chapter 5 and 6 of statistical rethinking and ignore the Bayesian modelling and read it only for the linear modelling learning that should tell you what you need to know. \n\nYou can also check “causal inference for the brave and true” chapter 1 and 2 then that should be a good starting point too. \n\nThat should fill you in, in the fastest time possible. (I.e that should get the weirdness surrounding linear models and the 2 major frameworks for causal inference.)",
"label": "r/datascience",
"dataType": "comment",
"communityName": "r/datascience",
"datetime": "2024-05-22",
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}