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As valuable as the Bayesian approach is, most statisticians see it as only a partial solution to a very large problem.
flagamuffin · 2068 days ago · link ·
I haven't read Silver's book, but I do understand Bayesian probabiliy. (And I'm a big fan of it.) I think the author of this article falls into the trap of forgetting that Silver is writing for the masses in the same way the writer of Freakonomics was. People attacked Freakonomics too for similar reasons (broad conclusions, some misleading details, etc). What critics need to keep in mind is that the book wouldn't sell if Silver bored America with too many explanations for statements that are, in the end, small and correct enough that we can take his word for them. Yes, and? That's entirely valid enough to be included in his book.Silver seems to be using “Bayesian” not to mean the use of Bayes’s theorem but, rather, the general strategy of combining many different kinds of information.
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There is evidence from neuroscience studies that we use this type of subjective Bayesian logic unconsciously every day, something similar to intuition. I think the author is using a very strict mathematical definition of Bayes' theorem whereas Silver is using it more colloquially. You are right that popular science can't be held to the same standard as peer reviewed science. I would argue that in science, it might be worthwhile to do a Fisher and a Bayes analysis, but unfortunately only Fisher (or some similar type test) is taken seriously.
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flagamuffin · 2068 days ago · link ·
There is evidence from neuroscience studies that we use this type of subjective Bayesian logic unconsciously every day, something similar to intuition.
I do this all the time, and when I realized I was doing it subconsciously -- attaching probabilities to events, factoring in conditions and opportunity cost -- I started to do it actively. Discovering LessWrong helped.
You are right that popular science can't be held to the same standard as peer reviewed science.
Malcolm Gladwell ran into the same problems.
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I think the problem with popular science is that the authors don't always make it clear that they're simplifying, and the reader comes away with a false sense or feeling like an expert. It's OK to simplify, but it needs to be clear that some nuance is missing.
I don't think this is the case anymore. Bayesian methods were fringe for a long time, but they've been mainstream for at least the last decade.I would argue that in science, it might be worthwhile to do a Fisher and a Bayes analysis, but unfortunately only Fisher (or some similar type test) is taken seriously.
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I don't know too much about Bayesian statistics. But after reading the book, it definitely got me intrigued and was a nice primer to it. Also, the book doesn't just solely talk about Bayesian principles. Silver provides a nice blend of modern examples where the 'signal' gets clouded by noise and whatnot. If anything, it teaches you the biases in thinking when making critical decisions. I would recommend the book