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Título:	Reasoning and choice in the Monty Hall Dilemma (MHD): implications for improving Bayesian reasoning
Autor/a:	Tubau Sala, Elisabet; Aguilar-Lleyda, David; Johnson, Eric D.
Otros autores:	Universitat de Barcelona
Abstract:	The Monty Hall Dilemma (MHD) is a two-step decision problem involving counterintuitive conditional probabilities. The first choice is made among three equally probable options, whereas the second choice takes place after the elimination of one of the non-selected options which does not hide the prize. Differing from most Bayesian problems, statistical information in the MHD has to be inferred, either by learning outcome probabilities or by reasoning from the presented sequence of events. This often leads to suboptimal decisions and erroneous probability judgments. Specifically, decision makers commonly develop a wrong intuition that final probabilities are equally distributed, together with a preference for their first choice. Several studies have shown that repeated practice enhances sensitivity to the different reward probabilities, but does not facilitate correct Bayesian reasoning. However, modest improvements in probability judgments have been observed after guided explanations. To explain these dissociations, the present review focuses on two types of causes producing the observed biases: Emotional-based choice biases and cognitive limitations in understanding probabilistic information. Among the latter, we identify a crucial cause for the universal difficulty in overcoming the equiprobability illusion: Incomplete representation of prior and conditional probabilities. We conclude that repeated practice and/or high incentives can be effective for overcoming choice biases, but promoting an adequate partitioning of possibilities seems to be necessary for overcoming cognitive illusions and improving Bayesian reasoning.
Materia(s):	-Probabilitats -Estadística bayesiana -Probabilities -Bayesian statistical decision
Derechos:	cc-by (c) Tubau Sala, Elisabet et al., 2015 http://creativecommons.org/licenses/by/3.0/es
Tipo de documento:	Artículo Artículo - Versión publicada
Editor:	Frontiers Media
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