Bayesian probability estimates are not necessary to make choices satisfying Bayes' rule in elementary situations

Frontiers in Psychology
Artur DomuratMarta Nowak-Przygodzka

Abstract

This paper has two aims. First, we investigate how often people make choices conforming to Bayes' rule when natural sampling is applied. Second, we show that using Bayes' rule is not necessary to make choices satisfying Bayes' rule. Simpler methods, even fallacious heuristics, might prescribe correct choices reasonably often under specific circumstances. We considered elementary situations with binary sets of hypotheses and data. We adopted an ecological approach and prepared two-stage computer tasks resembling natural sampling. Probabilistic relations were inferred from a set of pictures, followed by a choice which was made to maximize the chance of a preferred outcome. Use of Bayes' rule was deduced indirectly from choices. Study 1 used a stratified sample of N = 60 participants equally distributed with regard to gender and type of education (humanities vs. pure sciences). Choices satisfying Bayes' rule were dominant. To investigate ways of making choices more directly, we replicated Study 1, adding a task with a verbal report. In Study 2 (N = 76) choices conforming to Bayes' rule dominated again. However, the verbal reports revealed use of a new, non-inverse rule, which always renders correct choices, but is easier than Baye...Continue Reading

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Citations

Dec 24, 2015·Frontiers in Psychology·David R Mandel, Gorka Navarrete
Apr 22, 2017·Acta Psychologica·Michał Białek
Jun 2, 2020·Frontiers in Psychology·Lin YinShun Peng

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