| Probabilistic inference in human infants. | |
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MedLine Citation:
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PMID: 23205407 Owner: NLM Status: In-Process |
Abstract/OtherAbstract:
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In this chapter, we review empirical evidence in support of infants' ability to make rudimentary probabilistic inferences. A recent surge of research in cognitive developmental psychology examines whether human learners, from infancy through adulthood, reason in ways consistent with Bayesian inference. However, when exploring this question an important first step is to identify the available inference mechanisms and computational machinery that might allow infants and young children to make inductive inferences. A number of recent studies have asked if infants may be "intuitive statisticians," making inferences about the relationship between samples and populations in both looking-time and choice tasks. Furthermore, infants make these inferences under a variety of sampling conditions and integrate prior domain knowledge into their probability calculations. The competences demonstrated in the reviewed experiments appear to draw on an intuitive probability notion that is early emerging and does not appear to be available for conscious reflection. |
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Authors:
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Stephanie Denison; Fei Xu |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Advances in child development and behavior Volume: 43 ISSN: 0065-2407 ISO Abbreviation: Adv Child Dev Behav Publication Date: 2012 |
Date Detail:
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Created Date: 2012-12-04 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0370417 Medline TA: Adv Child Dev Behav Country: United States |
Other Details:
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Languages: eng Pagination: 27-58 Citation Subset: IM |
Affiliation:
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Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA. smdeniso@berkeley.edu |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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