Bayes' Theorem

Bayes' Theorem

Bayes's 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's 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 data that its truth renders probable — is the cornerstone of all subjectivist methodology.
1. Conditional Probabilities and Bayes's Theorem
2. Special Forms of Bayes's Theorem
3. The Role of Bayes's Theorem in Subjectivist Accounts of Evidence
4. The Role of Bayes's Theorem in Subjectivist Models of Learning
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