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 derived from the work of the Reverend Thomas Bayes.
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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.
Online tutorial with an introduction to probability theory and to Bayesian belief networks.
Probabilistic programming with a computation/understanding-first, mathematics-second point of view. Open source.
Part of the University of St. Andrews History of Mathematics archive.
Promotes the development and use of logical methods for the improvement of decision-making.
The institute has a strong focus on Bayesian statistics.
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.
A monumental online book by the late E. T. Jaynes on Bayesian inference. Also has a number of related articles by other authors.
Encyclopedia article on this system for describing epistemological uncertainty using the mathematical language of probability.
Encyclopedia article on the statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true.
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.
Part of the University of St. Andrews History of Mathematics archive.
Promotes the development and use of logical methods for the improvement of decision-making.
Probabilistic programming with a computation/understanding-first, mathematics-second point of view. Open source.
Online tutorial with an introduction to probability theory and to Bayesian belief networks.
Encyclopedia article on this system for describing epistemological uncertainty using the mathematical language of probability.
Encyclopedia article on the statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true.
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.
The institute has a strong focus on Bayesian statistics.
A monumental online book by the late E. T. Jaynes on Bayesian inference. Also has a number of related articles by other authors.
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