Bayesian inference is statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true. The name "Bayesian" comes from the frequent use of Bayes' theorem in the inference process. Bayes' theorem was first derived by the Reverend Thomas Bayes.
Evidence and changing beliefs
Bayesian statisticians believe that Bayesian inference uses aspects of the
scientific method, which involves collecting
evidence that is meant to be consistent or inconsistent with a given
hypothesis. As evidence accumulates, the degree of belief in a hypothesis changes. With enough evidence, it will often become very high or very low. Bayesian statisticians also believe that Bayesian inference is a suitable logical basis to discriminate between conflicting hypotheses. Hypotheses with a very high degree of belief should be accepted as true; those with a very low degree of belief should be rejected as false.
- An example of Bayesian inference is
- For billions of years, the sun has risen after it has set. The sun has set tonight. With very high probability (or I strongly believe that or it is true that) the sun will rise tomorrow. With very low probability (or I do not at all believe that or it is false that) the sun will not rise tomorrow.
Bayesian inference uses a numerical estimate of the degree of belief in a hypothesis before evidence has been observed and calculates a numerical estimate of the degree of belief in the hypothesis after evidence has been observed. Bayesian inference usually relies on degrees of belief, or subjective probabilities, in the induction process and does not necessarily claim to provide an objective method of induction. Nonetheless, some Bayesian statisticians believe probabilities can have an objective value and therefore Bayesian inference can provide an objective method of induction. See
scientific method.
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Bayesian Analysis - Twitter Search#plos The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis http://bit.ly/4WJQX5bookapharmacist (Kazeem Olalekan) Sun, 13 Dec 2009 01:55:48 -0000
#plos The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis http://bit.ly/4WJQX5
#plos The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis http://bit.ly/76RAfobookapharmacist (Kazeem Olalekan) Sat, 12 Dec 2009 21:55:39 -0000
#plos The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis http://bit.ly/76RAfo
#plos The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis http://bit.ly/4WJQX5bookapharmacist (Kazeem Olalekan) Sat, 12 Dec 2009 09:55:24 -0000
#plos The Severity of Pandemic H1N1 Influenza in the United States, from April to July 2009: A Bayesian Analysis http://bit.ly/4WJQX5
GenomeResearch: Bayesian network analysis of targeting interactions in chromatin [LETTERS]:
In .. http://bit.ly/8wwZmVgenomigence (genomigence) Sat, 12 Dec 2009 08:19:10 -0000
GenomeResearch: Bayesian network analysis of targeting interactions in chromatin [LETTERS]:
In .. http://bit.ly/8wwZmV
RT @fonnesbeck: "Some thoughts on the BUGS package for Bayesian analysis http://tinyurl.com/y89zxwu"healthyalgo (Abraham Flaxman) Fri, 11 Dec 2009 19:14:30 -0000
RT @fonnesbeck: "Some thoughts on the BUGS package for Bayesian analysis http://tinyurl.com/y89zxwu"
Some thoughts on the BUGS package for Bayesian analysis http://www.stat.columbia.edu/~gelman/research/published/bugsnext2.pdffonnesbeck (Chris Fonnesbeck) Fri, 11 Dec 2009 18:59:23 -0000
Some thoughts on the BUGS package for Bayesian analysis http://www.stat.columbia.edu/~gelman/research/published/bugsnext2.pdf
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International Society for Bayesian Analysis - Promotes the development and application of Bayesian statistical theory and methods useful in the solution of theoretical and applied problems in science, industry and government.
Bayesian Abstract Archive - An archive of abstracts of research papers on Bayesian statistics. Sponsored by ISBA and SBSS.
Bayesian Analysis Archive - Part of the ArXiv e-print repository.
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Bayesian Inference for the Physical Sciences - An annotated index for information on Bayesian inference for the physical sciences.
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Biography of Reverend Thomas Bayes (1702-1761) - Part of the University of St. Andrews History of Mathematics archive.
Meta Description: [ Thomas Bayes (1702-1761) ]
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Computational Technology for Bayesian Inference - Explains the benefits and method of integrating the sample distribution of a parameter space.
Decision Analysis Society - Promotes the development and use of logical methods for the improvement of decision-making.
Duke University Institute of Statistics and Decision Sciences - The institute has a strong focus on Bayesian statistics.
Measurement Decision Theory - Includes rules, examples, and information about adaptive testing and sequential decisions. Main ideas are presented using a binary classification (pass/fail) test and a sample three-item test.
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Non-subjective Bayesian Statistical Methodology - A website and mailing list on non-subjective priors (e.g. non-informative, conventional and reference priors).
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