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Collectivist Foundations for Bayesian Statistics

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
Creators:
CreatorsEmailORCID
Mayo-Wilson, Conorconormw@uw.edu
Saraf, Adityasarafa@uw.edu
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
Depositing User: Dr. Conor Mayo-Wilson
Date Deposited: 10 Jan 2021 03:22
Last Modified: 10 Jan 2021 03:22
Item ID: 18592
Subjects: General Issues > Decision Theory
Specific Sciences > Probability/Statistics
General Issues > Social Epistemology of Science
Date: 6 December 2020
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/18592

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