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Bayesian Probability (view source)
Revision as of 17:15, November 14, 2009
, 17:15, November 14, 2009Reverted edits by RyanMatthews (Talk) to last version by RJJensen
'''Bayesian probability''' is a particular calculus of inductive plausible reasoning based on the works of [[Jacob Bernoulli|Bernoulli]], [[Rev Thomas Bayes|Bayes]], [[Pierre Simon de Laplace|Laplace]] (and more recently of [[Sir Harold Jeffreys|Jeffreys]], [[Richard T. Cox|Cox]], and [[Edwin T. Jaynes|Jaynes]]) in which probability is interpreted as the degree that a proposition/hypothesis/model is true ranging from complete certainty to complete certainty of its falsehood and all intermediate values. Unlike frequentist statistics, Bayesian statistics starts from initial "estimates" of probabilities, which may reflect anecdotal evidence and/or ideology. Probabilities are revised as evidence is accumulated.
'''Bayesian probability''' is a particular calculus of inductive plausible reasoning based on the works of [[Jacob Bernoulli|Bernoulli]], [[Rev Thomas Bayes|Bayes]], [[Pierre Simon de Laplace|Laplace]] (and more recently of [[Sir Harold Jeffreys|Jeffreys]], [[Richard T. Cox|Cox]], and [[Edwin T. Jaynes|Jaynes]]) in which probability is interpreted as the degree that a proposition/hypothesis/model is true ranging from complete certainty to complete certainty of its falsehood and all intermediate values.
[[category:Probability and Statistics]]
[[category:Probability and Statistics]]