Mayo-Wilson, Conor and Saraf, Aditya (2020) Collectivist Foundations for Bayesian Statistics. [Preprint]
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Abstract
What (if anything) justifies the use of Bayesian statistics in science? The traditional answer is that Bayesian statistics is simply an instance of orthodox expected utility theory. Thus, Bayesian statistical methods, like principles of utility theory, are justified by norms of individual rationality. In particular, most Bayesians argue that a scientist's credences must satisfy the probability axioms if she adheres to norms of practical and epistemic (individual) rationality. We argue that, to justify Bayesian statistics as a tool for science, it is necessary that a scientist's public credences (i.e., her degrees of belief qua scientist) obey the probability axioms. We claim that norms of collective science help justify this restricted view, termed public probabilism.
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| Item Type: | Preprint | |||||||||
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| Keywords: | Bayesian, statistics, prior probability, Dutch Book, accuracy, measurement theory | |||||||||
| Subjects: | General Issues > Decision Theory Specific Sciences > Probability/Statistics General Issues > Social Epistemology of Science |
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| Depositing User: | Dr. Conor Mayo-Wilson | |||||||||
| Date Deposited: | 07 Dec 2020 16:03 | |||||||||
| Last Modified: | 07 Dec 2020 16:03 | |||||||||
| Item ID: | 18496 | |||||||||
| Subjects: | General Issues > Decision Theory Specific Sciences > Probability/Statistics General Issues > Social Epistemology of Science |
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| Date: | 6 December 2020 | |||||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/18496 |
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