Re:Bayes’ Theorem – What is it and what is it good for?
by dimino on Friday June 26, 2015 @11:29AM
(#9785169)
I don't think it's as rigorously defined as it's purported to be. I just envision the practical application of manipulating values to produce desired results, and then post-hoc rationalizing those value manipulations to obtain a higer-than-warranted level of confidence in the result, because, "I applied rigor!"
Re:Bayes’ Theorem – What is it and what is it good for?
by darkxanthos on Friday June 26, 2015 @11:54AM
(#9785450)
The math is well defined and rigorous not every analysis that uses it. I think you're conflating those two things.
Re:Bayes’ Theorem – What is it and what is it good for?
by davidgerard on Friday June 26, 2015 @12:21PM
(#9785704)
He's talking about the practical effects of fallible humans using the version of Bayes advocated in the original post (citing Yudkowsky and Muehlhauser).
Pulling numbers out of your backside and running them through a process makes you more confident than just pulling them out of your backside directly, but I've yet to see evidence it does more than increasing your confidence.
1. Bayesian statistics allows use of "uninformative" priors. 2. Discarding your subjective beliefs is less than ideal as well as overweighting them. You have beliefs due to your experience. Weight them lightly but still use them. In the absence of much information your calculations will follow your gut. What else do you have in the absence of other information?
Using quantified subjective beliefs at least has the advantage of enabling you to make consistent choices based on what you know within a rigorously defined framework.