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Probability biases as Bayesian inference

By Andre

Abstract

In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed

Topics: weighting functions, probabilistic biases, adaptive probability theory.NAKeywords, Psychology, BF1-990, Philosophy. Psychology. Religion, B, DOAJ:Psychology, DOAJ:Social Sciences, Economic theory. Demography, HB1-3840, Social Sciences, H, DOAJ:Economics, DOAJ:Business and Economics, Economics as a science, HB71-74
Publisher: Society for Judgment and Decision Making
Year: 2006
OAI identifier: oai:doaj.org/article:1c472ba762244880a1afe9dff8b55518
Journal:
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