Research article summary (published 29 Jun 2009):

An encounter frequency account of how experience affects likelihood estimation.

Full Abstract

When making judgments, people often favor information received from a few individual sources over large-sample statistical data. Individual information is usually acquired piece by piece, whereas statistical information combines many observations into a single summary. We examined whether this difference in the frequency of encounters affects how data are weighted. In two experiments, subjects read statistical information indicating an event to be rare and contrasting information from individual cases suggesting the event to be common. We controlled whether the individual cases were summarized into a single summary like statistical information, or presented serially, case by case. Subjects' estimates of event frequencies were higher when the individual cases were presented in serial, rather than summarized, format. A third study demonstrated that subjects treat each data sample as an instance, and do not weight according to sample size. These results support the conclusion that people weight information according to encounter frequency.

Author information

Author/s: Obrecht, Natalie A (NA); Chapman, Gretchen B (GB); Gelman, Rochel (R);

Affiliation: Psychology Department, Rutgers University, Piscataway, New Jersey 08854-8020, USA. natalie(-atsign-)ruccs.rutgers.edu

Journal and publication information

Publication Type: Journal Article

Journal: Memory & cognition (Mem Cognit), published in United States. (Language: eng)

Reference: 2009-Jul; vol 37 (issue 5) : pp 632-43

Dates: Created 2009/06/02; Completed 2009/08/14;

PMID: 19487755, status: MEDLINE (last retrieval date: 8/21/2009, IMS Date: )

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

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Comprehension Humans Judgment Likelihood Functions Persuasive Communication

Persuasive Communication Probability Learning Problem Solving Reading Uncertainty

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