A rational analysis of the selection task as optimal data selection.

Human reasoning in hypothesis-testing tasks like Wason's (1966, 1968) selection task has been depicted as prone to systematic biases. However, performance on this task has been assessed against a now outmoded falsificationist philosophy of science. Therefore, the experimental data is reassessed in...

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Detalles Bibliográficos
Publicado en:Psychological Review Vol. 101; pp. 608 - 632
Autores principales: Oaksford, Mike, Chater, Nick
Formato: Artículo
Publicado: American Psychological Association October 1994
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: October 1994
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      pub: American Psychological Association
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        10.1037/0033-295X.101.4.608
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          Oaksford, Mike
          Chater, Nick
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        Cognition
        Problem solving
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          Cognition
          Problem solving
      ab: Human reasoning in hypothesis-testing tasks like Wason's (1966, 1968) selection task has been depicted as prone to systematic biases. However, performance on this task has been assessed against a now outmoded falsificationist philosophy of science. Therefore, the experimental data is reassessed in the light of a Bayesian model of optimal data selection in inductive hypothesis testing. The model provides a rational analysis (Anderson, 1990) of the selection task that fits well with people's performance on both abstract and thematic versions of the task. The model suggests that reasoning in these tasks may be rational rather than subject to systematic bias. Reprinted by permission of the publisher.
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    language: English
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