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 ?
Another concept that is key to addressing practical applications of Bayes' Theorem is Monte Carlo integration.
An alternative statement of Bayes' theorem explains it in terms of odds.
Applying Bayes | Police detectives generally understand the concepts behind Bayes' Theorem, even if they do not know the mathematical or quantitative formulation.
Bayes' theorem combines all the elements required to derive a probability that a hypothesis is true, including considerations of study power.
Evaluate the distribution curve for each estimate using Bayes' Theorem.
Combining the objectivity of likelihood ratios with subjective pretest probabilities using Bayes' theorem is consistent with the principles of evidence-based medicine.
The hyperparameter vector [alpha] can also be optimized by applying Bayes' theorem (level-2 inference).
Bayes' Theorem tells us that her posterior belief that the hypothesis (in this case, that the magnitude of harm lies between 1.
6) A simple statement of Bayes' Theorem uses three terms.
Bayes' Theorem and Aristotle's Efficient-Final Cause Symmetry
Then Bayes' theorem was used to establish various decision rules.
The quantitative mechanism for absorbing data-evidence to alter our scientific belief is provided by Bayes' theorem (although the same theorem can also be applied only to relative frequencies, conditioning within a frequentist sample space - a different application altogether).