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Course Topic(s): Probability | Basic Probability, conditional probability
This is a very short article on Bayesian odds. Bayes' theorem is used to derive a formula for the ratio of posterior probabilities \(P(A | C) / P(B | C)\) in terms of the prior probabilities \(P(A\)), \(P(B)\) and the conditional \( P(C | A)\) and \(P(C | B)\). An application is given to a ball and urn model. Unlike other Cut-the-Knot articles, this one uses MathJax for the mathematical notation, so the notation is rendered nicely.
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Creator(s): Alexander Bogomolny
Contributor(s): Alexander Bogomolny
This resource was cataloged by Kyle SiegristPublisher:
Resource copyright: Copyright Alexander Bogomolny. The HTML page can be accessed and linked to, but not copied or used in other works.
This review was published on September 14, 2012
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