Bayes' theorem

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Related to Bayes' rule: Bayes' formula

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 ?
Overall, subjects who purchased insurance chose consistently with Bayes' Rule about 98 percent of the time.
1980, Bayes' Rule as a Descriptive Model: The Representativeness Heuristic, Quarterly Journal of Economics, 95: 537-557.
In one frequently cited example, Grether (1980) finds evidence that people give less weight to base rates than Bayes' Rule requires when solving statistical problems that require them to weigh prior information and sample information.
We are interested in whether decisions are more consistent with Bayes' Rule when subjects are given the option to purchase insurance.
181) And while Bayes' rule tells us that the prior probability of "database guilt" plays a central role in calculating the defendant's posterior source probability, litigants have not sufficiently engaged on the radically different priors that can be produced from estimates based on different structural or survey methods.
We discuss Bayes' rule in Part II and note 43 below.
See infra text accompanying notes 39-42 (discussing how Bayes' rule combines these two types of information).
1], the central bank updates beliefs using Bayes' rule.
In this article I assume that the monetary authority makes decisions without fully knowing the effect of monetary policy on the economic environment but learns about it over time using Bayes' rule.
Once we have new information, Bayes' rule provides the updated
prior odds are 1:2), then Bayes' rule tells us (via equation (4))
Bayes' rule says that to derive the updated, posterior odds of