David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Stanford Encyclopedia of Philosophy (2008)
Bayes' Theorem is a simple mathematical formula used for calculating conditional probabilities. It figures prominently in subjectivist or Bayesian approaches to epistemology, statistics, and inductive logic. Subjectivists, who maintain that rational belief is governed by the laws of probability, lean heavily on conditional probabilities in their theories of evidence and their models of empirical learning. Bayes' Theorem is central to these enterprises both because it simplifies the calculation of conditional probabilities and because it clarifies significant features of subjectivist position. Indeed, the Theorem's central insight — that a hypothesis is confirmed by any body of data that its truth renders probable — is the cornerstone of all subjectivist methodology
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Michael Schippers (2014). Probabilistic Measures of Coherence: From Adequacy Constraints Towards Pluralism. Synthese 191 (16):3821-3845.
Jakob Koscholke (2016). Evaluating Test Cases for Probabilistic Measures of Coherence. Erkenntnis 81 (1):155-181.
Tobias Starzak (forthcoming). Interpretations Without Justification: A General Argument Against Morgan’s Canon. Synthese:1-21.
David H. Glass & Mark McCartney (2015). A New Argument for the Likelihood Ratio Measure of Confirmation. Acta Analytica 30 (1):59-65.
Elliott Sober (2011). Responses to Fitelson, Sansom, and Sarkar. [REVIEW] Philosophy and Phenomenological Research 83 (3):692-704.
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