# Bayes' theorem

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Related to Bayes' theorem: conditional probability

## Bayes' theorem

[bāz′]
Etymology: Thomas Bayes, British mathematician, 1702-1761
a mathematic statement of the relationships of test sensitivity, specificity, and the predictive value of a positive test result. The predictive value of the test is the number that is useful to the clinician. A positive result demonstrates the conditional probability of the presence of a disease.

## theorem

(the'o-rem) [Gr. theorema, principle arrived at by speculation]
A proposition that can be proved by use of logic, or by argument, from information previously accepted as being valid.

### Bayes' theorem

See: Bayes' theorem.
References in periodicals archive ?
An alternative statement of Bayes' theorem explains it in terms of odds.
It is clear that while Bayes' theorem could provide a normative approach to legal decision making in the context of causation and medicinal products, implementing the theorem, in practice, is likely to be difficult.
Evaluate the distribution curve for each estimate using Bayes' Theorem.
If we assume that the presumption of innocence standard would require the prior probability of guilt to be zero, the probability of paternity in a criminal case would always be zero because Bayes' Theorem requires the paternity index to be multiplied by a positive prior probability in order to have any utility.
Bayes' theorem, in which the base rate factors into a relatively complex calculation of the one-time probability of having breast cancer given a positive mammography, yields a prediction of 7.
Coverage includes Bayes' theorem, graphical fits to measured data, fractals and their applications, Monte Carlo methods, and application of statistics to image quality measurements.
They consider basic concepts such as null and alternative hypotheses, p-value, significance level, and power; and such topics as sample selection, linear regression, the analysis of variance, maximum likelihood, Bayes' theorem, meta-analysis, and the bootstrap.
George Diamond and employs Bayes' theorem to analyze and report results of various clinical descriptors and noninvasive tests relative to the diagnosis of coronary artery disease.
introduces statistical techniques used for understanding business and the social sciences, including basic probability tools, ways to summarize data using charts and graphs and summary statistics, Bayes' theorem, sampling, estimation, confidence intervals, hypothesis testing for one and two samples, contingency tables, goodness-of-fit, analysis of variance, and population variances.

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