Philosophy of Science 16 - Bayesian Epistemology 2

[@WorthlessWinner]

Can't you have a Bayesian epistemology that allows mathematical truths to have values between 0 and 1, especially if it is subjective? It would make us uncertain about the foundations of the epistemology, but we're accepting uncertainty anyway when using this so it doesn't seem much of an added issue.

[@Ansatz66]

Bayes' theorem makes a lot of sense when we've got meaningful probabilities to plug into the formula. Bayesian epistemology would have us conclude that Bayes' theorem still makes sense even when we plug in meaningless numbers in place of the probabilities. P(H | E) = P(E | H) P(H) / P(E), where P(H) = whatever random number between 0 and 1, and P(E) is also whatever feels good at the moment, and P(E | H) is specified by H. So much in this is left to the whim of the individual doing the analysis, yet we're somehow supposed to take seriously that whether P(H | E) > P(H) determines whether H is confirmed by E.

[@EdoardoMarcora]

Don't we use prior a probability distribution for the prior (rather than a single value) when we do bayesian inference? A uniform between 0-1 would describe the agnostic scenario... Or am I missing something?

[@erinrobertson1800]

what about the fact that Bayesianism rests on the rules of probability and we have to use induction to show that they will continue to hold. Hence it presupposes uniformity principle and is circular

[@Noddy1103]

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