Definition of Bayes' Theorem:
In probability theory as well as statistics, Bayes' theorem (also called Bayes' law and/or Bayes' rule) is a result that is of great importance in the mathematical manipulation of conditional probabilities. It is a result that derives from the more basic axioms of probability.
When applied, the probabilities involved in Bayes' theorem may have any of a number of probability interpretations. In one of these interpretations, Bayes' theorem is used directly as part of a particular approach to statistical inference. In particular, with the Bayesian interpretation of probability, the theorem expresses how a subjective degree of belief should rationally change to account for evidence: this is Bayesian inference, and it is fundamental to Bayesian statistics. Keep in mind, however, that Bayes' theorem has applications in a wide range of calculations involving probabilities, not just in Bayesian inference.
See Also: Wikipedia Bayes' Theorem.
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In probability theory as well as statistics, Bayes' theorem (also called Bayes' law and/or Bayes' rule) is a result that is of great importance in the mathematical manipulation of conditional probabilities. It is a result that derives from the more basic axioms of probability.
When applied, the probabilities involved in Bayes' theorem may have any of a number of probability interpretations. In one of these interpretations, Bayes' theorem is used directly as part of a particular approach to statistical inference. In particular, with the Bayesian interpretation of probability, the theorem expresses how a subjective degree of belief should rationally change to account for evidence: this is Bayesian inference, and it is fundamental to Bayesian statistics. Keep in mind, however, that Bayes' theorem has applications in a wide range of calculations involving probabilities, not just in Bayesian inference.
See Also: Wikipedia Bayes' Theorem.
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