by Bayesianism — a wrong-headed pseudoscience The occurrence of unknown prior probabilities, that must be stipulated arbitrarily, does not worry the Bayesian anymore than God’s inscrutable designs worry the theologian. Thus Lindley (1976), one of the leaders of the Bayesian school, holds that this difficulty has been ‘grossly exaggerated’. And he adds: ‘I am often asked if the [Bayesian] method gives the right answer: or, more particularly, how do you know if you have got the right prior [probability]. My reply is that I don’t know what is meant by ‘right’ in this context. The Bayesian theory is about coherence, not about right or wrong.’ Thus the Bayesian, along with the philosopher who only cares about the cogency of arguments, fits in with the reasoning
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Lars Pålsson Syll considers the following as important: Theory of Science & Methodology
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Bayesianism — a wrong-headed pseudoscience
The occurrence of unknown prior probabilities, that must be stipulated arbitrarily, does not worry the Bayesian anymore than God’s inscrutable designs worry the theologian. Thus Lindley (1976), one of the leaders of the Bayesian school, holds that this difficulty has been ‘grossly exaggerated’. And he adds: ‘I am often asked if the [Bayesian] method gives the right answer: or, more particularly, how do you know if you have got the right prior [probability]. My reply is that I don’t know what is meant by ‘right’ in this context. The Bayesian theory is about coherence, not about right or wrong.’ Thus the Bayesian, along with the philosopher who only cares about the cogency of arguments, fits in with the reasoning madman …
One should not confuse the objective probabilities of random events with mere intuitive likelihoods of such events or the plausibility (or verisimilitude) of the corresponding hypotheses in the light of background knowledge. As Peirce (1935: p. 363) put it, this confusion ‘is a fertile source of waste of time and energy’. A clear case of such waste is the current proliferation of rational-choice theories in the social sciences, to model processes that are far from random, from marriage to crime to business transactions to political struggles.