Any curriculum or book recommendations? Also curious about how much beyond 'Stats 101' (hypothesis testing, etc) you think is important :)
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I recommend
@AllenDowney's Think Bayes and Think Stats. In terms of how far to go, I hit diminishing returns to programming and infrastructure far before stats. Stats-wise I still feel like I'm getting nice payoffs to learning. - Još 3 druga odgovora
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Yeah, I think so too. I'm all for more folks doing applied math. It's a great tool. The last thing I'd want is to keep folks out, but there's a lot of bad info and I see many in the danger zone.
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I don't know if he is even a faker, but he writes complete garbage. He tries to be edgy and it falls completely flat or something.
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What's disturbing is that it must work, he's been at it for a while.
- Još 1 odgovor
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But don't learn from that
@DataScienceCtrl article which is WAY off the mark.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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All you need to know is the Statistical Holy Trinity: 1. Maximum Likelihood Estimation 2. Likelihood Ratio Testing 3. Fisher Information Matrix approximation of the Standard Error Ellipsiod.
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That's basically the syllabus of every graudate mathematics course in statistical inference.
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Also, Vincent Granville can be seriously odious in his own right. Enough that we should his avoid his work. See this from
@BecomingDataSci https://www.becomingadatascientist.com/2014/07/01/something-has-been-bothering-me-about-data-science-central/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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