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The description–experience gap in risky choice: the role of sample size and experienced probabilities
Author(s) -
Hau Robin,
Pleskac Timothy J.,
Kiefer Jürgen,
Hertwig Ralph
Publication year - 2008
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.598
Subject(s) - heuristics , set (abstract data type) , sample (material) , psychology , sample size determination , sampling (signal processing) , choice set , computer science , econometrics , cognitive psychology , statistics , economics , mathematics , chemistry , filter (signal processing) , chromatography , computer vision , programming language , operating system
Risky prospects come in different forms. Sometimes options are presented with convenient descriptions summarizing outcomes and their respective likelihoods. People can thus make decisions from description . In other cases people must call on their encounters with such prospects, making decisions from experience . Recent studies report a systematic and large description–experience gap. One key determinant of this gap is people's tendency to rely on small samples resulting in substantial sampling error. Here we examine whether this gap exists even when people draw on large samples. Although smaller, the gap persists. We use the choices of the present and previous studies to test a large set of candidate strategies that model decisions from experience, including 12 heuristics, two associative‐learning models and the two‐stage model of cumulative prospect theory. This model analysis suggests—as one explanation for the remaining description–experience gap in large samples—that people treat probabilities differently in both types of decisions. Copyright © 2008 John Wiley & Sons, Ltd.