Introduction and examples

Part of the Springer Texts in Statistics book series (STS)


We often use probabilities informally to express our information and beliefs about unknown quantities. However, the use of probabilities to express information can be made formal: In a precise mathematical sense, it can be shown that probabilities can numerically represent a set of rational beliefs, that there is a relationship between probability and information, and that Bayes’ rule provides a rational method for updating beliefs in light of new information. The process of inductive learning via Bayes’ rule is referred to as Bayesian inference.


Ordinary Little Square Posterior Distribution Prior Distribution Bayesian Inference Prior Belief 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of WashingtonSeattleUSA

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