An associative framework for probability judgment: an application to biases.

Full Abstract

Three experiments show that understanding of biases in probability judgment can be improved by extending the application of the associative-learning framework. In Experiment 1, the authors used M. A. Gluck and G. H. Bower's (1988a) diagnostic-learning task to replicate apparent base-rate neglect and to induce the conjunction fallacy in a later judgment phase as a by-product of the conversion bias. In Experiment 2, the authors found stronger evidence of the conversion bias with the same learning task. In Experiment 3, the authors changed the diagnostic-learning task to induce some conjunction fallacies that were not based on the conversion bias. The authors show that the conjunction fallacies obtained in Experiment 3 can be explained by adding an averaging component to M. A. Gluck and G. H. Bower's model.

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Author information

Author/s: Cobos, Pedro L (PL); Almaraz, Julián (J); García-Madruga, Juan A (JA);

Affiliation: Departamento de Psicología Básica, Facultad de Psicología, Universidad de Málaga, Spain. p_cobos(-atsign-)uma.es

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Journal of experimental psychology. Learning, memory, and cognition (J Exp Psychol Learn Mem Cogn), published in United States. (Language: eng)

Reference: 2003-Jan; vol 29 (issue 1) : pp 80-96

Dates: Created 2003/01/28; Completed 2003/05/01; Revised 2006/11/15;

PMID: 12549585, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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