Definition of Bayes' theorem in English:

Bayes' theorem

nounˈbeɪz θɪərəmˈbāz ˌTHēərəm

Statistics

A theorem describing how the conditional probability of each of a set of possible causes for a given observed outcome can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause.
Example sentencesExamples
- The projections of the four individual submodels were integrated into a single prediction based upon Bayes' theorem.
- To summarize the principle of our approach, we used Bayes' theorem to rewrite the posterior pdf as a function of a prior and a likelihood.
- Once these parameters have been estimated, Bayes' theorem is used to estimate the posterior probability that a given site came from the class of positively selected sites.
- Following Bayes' theorem, the posterior distribution over the parameter space is proportional to the likelihood times the prior distribution.
- A follower of Clifford might object if there was no philosophical discussion of rival explanations or of the application here of Bayes' theorem in the theory of probability.

Origin

Mid 19th century: named after Thomas Bayes (1702–61), English mathematician.

Definition of Bayes' theorem in US English:

Bayes' theorem

nounˈbāz ˌTHēərəm

Statistics

A theorem describing how the conditional probability of each of a set of possible causes for a given observed outcome can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause.
Example sentencesExamples
- Once these parameters have been estimated, Bayes' theorem is used to estimate the posterior probability that a given site came from the class of positively selected sites.
- To summarize the principle of our approach, we used Bayes' theorem to rewrite the posterior pdf as a function of a prior and a likelihood.
- Following Bayes' theorem, the posterior distribution over the parameter space is proportional to the likelihood times the prior distribution.
- The projections of the four individual submodels were integrated into a single prediction based upon Bayes' theorem.
- A follower of Clifford might object if there was no philosophical discussion of rival explanations or of the application here of Bayes' theorem in the theory of probability.

Origin

Mid 19th century: named after Thomas Bayes (1702–61), English mathematician.

单词	Bayes' theorem
释义	Definition of Bayes' theorem in English: Bayes' theorem nounˈbeɪz θɪərəmˈbāz ˌTHēərəm Statistics A theorem describing how the conditional probability of each of a set of possible causes for a given observed outcome can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause. Example sentencesExamples The projections of the four individual submodels were integrated into a single prediction based upon Bayes' theorem. To summarize the principle of our approach, we used Bayes' theorem to rewrite the posterior pdf as a function of a prior and a likelihood. Once these parameters have been estimated, Bayes' theorem is used to estimate the posterior probability that a given site came from the class of positively selected sites. Following Bayes' theorem, the posterior distribution over the parameter space is proportional to the likelihood times the prior distribution. A follower of Clifford might object if there was no philosophical discussion of rival explanations or of the application here of Bayes' theorem in the theory of probability. Origin Mid 19th century: named after Thomas Bayes (1702–61), English mathematician. Definition of Bayes' theorem in US English: Bayes' theorem nounˈbāz ˌTHēərəm Statistics A theorem describing how the conditional probability of each of a set of possible causes for a given observed outcome can be computed from knowledge of the probability of each cause and the conditional probability of the outcome of each cause. Example sentencesExamples Once these parameters have been estimated, Bayes' theorem is used to estimate the posterior probability that a given site came from the class of positively selected sites. To summarize the principle of our approach, we used Bayes' theorem to rewrite the posterior pdf as a function of a prior and a likelihood. Following Bayes' theorem, the posterior distribution over the parameter space is proportional to the likelihood times the prior distribution. The projections of the four individual submodels were integrated into a single prediction based upon Bayes' theorem. A follower of Clifford might object if there was no philosophical discussion of rival explanations or of the application here of Bayes' theorem in the theory of probability. Origin Mid 19th century: named after Thomas Bayes (1702–61), English mathematician.
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