101–110 of 138 posts
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That's a great textbook!
It's been recommended on this topic several times, so I'm looking at it. Quite expensive ! I see there is a series of lectures, which seems identical to the book. Is it the same ? Or still worth buying the book ?
Statistics education is undergoing a bit of a revolution, driven by the accessibility of computers. For example, hypothesis testing is introduced by randomization[1], using a randomized permutation test[2]. I find this really easy to understand, compared to how I learned statistics using a more traditional approach. The traditional approach taught be a cookbook of hypothesis tests to use: use the t-test in this situa…
The difficulty of teaching statistics is that the maths you need to prove things are right and gain an intuitive understanding of the methods are far more advanced than what is presented in a basic stats course. Gosset came up with the t-test and proved to the world it made sense, yet we teach students to apply it in a black box way without a fundamental understanding of why it's right. That's not great pedagogy. IMO…
This is an odd way of putting it. I think it's better to say that, given some mostly uncontroversial assumptions, if one is willing to assign real number degrees of belief to uncertain claims, then Bayesian statistical inference is the only way of reasoning about those claims that's compatible with classical propositional logic.
As much as I appreciate and love all pedagogical endeavours in the field, especially in the form of open texts, I really, really, really dislike this overall approach to teaching introductory statistics. I'm hoping to see, over time, a shift away from ad-hoc null hypothesis testing in favour of linear models (yes, in introductory courses, from the start-- see link below) and Bayesian-by-default approaches. https://li…
> I'm hoping to see, over time, a shift away from ad-hoc null hypothesis testing in favour of linear models (yes, in introductory courses, from the start-- see link below) and Bayesian-by-default approaches. Is there anything where I can start today, as a guinea pig? My statistics education is basically zero.
Earlier quoted context omitted.
The difficulty of teaching statistics is that the maths you need to prove things are right and gain an intuitive understanding of the methods are far more advanced than what is presented in a basic stats course. Gosset came up with the t-test and proved to the world it made sense, yet we teach students to apply it in a black box way without a fundamental understanding of why it's right. That's not great pedagogy. IMO…
Maximum likelihood (which underpins many frequentist methods) basically amounts to Bayesian statistics with a uniform prior on your parameters. And the "shape" of your prior actually depends on the chosen parametrization, so in principle you can account for non-flat priors as well.
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It's been recommended on this topic several times, so I'm looking at it. Quite expensive ! I see there is a series of lectures, which seems identical to the book. Is it the same ? Or still worth buying the book ?
The lectures are good, and I've been told the book can be found online by the intrepid. I guess that Anna's Archive or Library Genesis has it.
It's here: https://civil.colorado.edu/~balajir/CVEN6833/bayes-resources...
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Yes, parents can be horrible too. Unfortunately it's somehow socially acceptable and even worthy of pride in some circles, to be "bad at math". It's seems very rare for someone to openly say "I'm bad at [my native language]" or "writing". I feel stats is has a somewhat similar effect even among those with math education. Several friends who have a degree in math recoil at the first mention of stats concepts.
> It's seems very rare for someone to openly say "I'm bad at [my native language]" or "writing". It is actually even fashionable in non-english countries. Declaring "I'm bad at [my native language], I only use english anyway" makes you a better person somehow. And it's not rare in other areas either – in post-truth world it's trendy not to know things.
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The lectures are good, and I've been told the book can be found online by the intrepid. I guess that Anna's Archive or Library Genesis has it.
I've found the book indeed - although it seems to be the first edition. It's here: https://civil.colorado.edu/~balajir/CVEN6833/bayes-resources...
This is the third result from a query I ran:
https://github.com/Booleans/statistical-rethinking/blob/mast...
Main repo w/ some notebooks: https://github.com/Booleans/statistical-rethinking
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> It's seems very rare for someone to openly say "I'm bad at [my native language]" or "writing". It is actually even fashionable in non-english countries. Declaring "I'm bad at [my native language], I only use english anyway" makes you a better person somehow. And it's not rare in other areas either – in post-truth world it's trendy not to know things.
In non-english countries? All of them? Source? I, as a person from one of said non-english countries, disagree.
Not that he was bad at German, necessarily, but that it was overly complex vs English, so he and his significant other even used English at home when they both didn't have to.
This is just one example, of course.
I was actually surprised to hear him say that (though it may have been to thwart my attempts at speaking some German when we had a meeting. I don't know any German,lol).
What is a good book on statistics that one can use for self-learning?
https://pubs.aip.org/aip/cip/article-abstract/3/5/106/136800...