Bayesianism for humans: "probable enough"
(followup to What Bayesianism has taught me? and Bayesianism for Humans) There are two insights from Bayesianism which occurred to me and which I hadn't seen anywhere else before. I like lists in the two posts linked above, so for the sake of completeness, I'm going to add my two cents to a public domain. Second penny is here. "Probable enough" When you have eliminated the impossible, whatever remains is often more improbable than your having made a mistake in one of your impossibility proofs. Steven Kaas Bayesian way of thinking introduced me to the idea of "hypothesis which is probably isn't true, but probable enough to rise to the level of conscious attention" — in other words, to the situation when P(H) is notable but less than 50%. Looking back, I think that the notion of taking seriously something which you don't think is true was alien to me. Hence, everything was either probably true or probably false; things from the former category were over-confidently certain, and things from the latter category were barely worth thinking about. This model was correct, but only in a formal sense. Suppose you are living in Gotham, the city famous because of it's crime rate and it's masked (and well-funded) vigilante, Batman. Recently you had read The Better Angels of Our Nature: Why Violence Has Declined by Steven Pinker, and according to some theories described here, Batman isn't good for Gotham at all. Now you know, for example, the theory of Donald Black that "crime is, from the point of view of the perpetrator, the pursuit of justice". You know about idea that in order for crime rate to drop, people should perceive their law system as legitimate. You suspect that criminals beaten by Bats don't perceive the act as a fair and regular punishment for something bad, or an attempt to defend them from injustice; instead the act is perceived as a round of bad luck. So, the criminals are busy plotting their revenge, not internalizing civil norms. You
Thank you. English isn't my first language, so for me feedback means a lot. Especially positive :)
My point was that representative heuristic made two errors: firstly, it violates "ratio rule" (= equates P(S|c) and P(c|S)), and secondly, sometimes it replaces P(c|S) with something else. That means that the popular idea "well, just treat it as P(c|S) instead of P(S|c); if you add P(c|~S) and P(S), then everything will be OK " doesn't always work.
The main point of our disagreement seem to be this:
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