| bayes theorem | A theorem in probability theory named for thomas bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihoods of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. (12 Dec 1998) |
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| Bayes, Thomas | <person> British mathematician, 1702-1761. See: Bayes theorem. (05 Mar 2000) |
| Bayesian hypothesis | An array of surmised values of a parameter to be severally explored in the light of a current set of data, with logical symmetry being preserved among all. The merits of each hypothesis entertained are based on quantity, the prior probability. The probability of the data conditional on the hypothesis is computed as the conditional probability for each; the product of the two for each hypothesis is the joint probability, and the ratio of each joint probability to the sum of all the joint probabilities is the posterior probability for that hypothesis. Unlike the Neyman-Pearson test of hypotheses, the answer is a statement about the hypothesis, not about the sample conditional on the hypothesis. No hypothesis is preferred or prevails by default. The procedure may be applied recursively any number of times, as the data becomes available. (05 Mar 2000) |
Synonyms : Analysis, Bayesian, Forecast, Bayesian, Method, Bayesian, Prediction, Bayesian, Theorem, Bayes
| Bayes' theorem |
(statistics) a theorem describing how the conditional probability of a set of possible causes for a given observed event can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause
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| bayesian |
of or relating to statistical methods based on Bayes' theorem
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| Bayes' theorem |
A theorem (formula) that is used to compute posterior probabilities by revising prior probabilities. (page 784)
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| bayesian statistics |
An area of statistics that uses Bayes' theorem to update prior belief about a probability or population parameter to posterior belief. (page 785)
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| Bayes' theorem |
SEE: Bayes' theorem..
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