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Chapter 5 - The J/DM Separation Paradox and the Reliance on the Small Samples Hypothesis

from Part II - Sampling Mechanisms

Published online by Cambridge University Press:  01 June 2023

By
Ido Erev  and
Ori Plonsky
Edited by
Klaus Fiedler ,
Peter Juslin  and
Jerker Denrell
Klaus Fiedler
Affiliation:
Universität Heidelberg
Peter Juslin
Affiliation:
Uppsala Universitet, Sweden
Jerker Denrell
Affiliation:
University of Warwick
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Summary

Previous research demonstrates a large difference between decisions from description and decisions from experience, and also between decisions and probability judgment from experience. Comparison of decisions from description and from experience reveals a description–experience gap (Hertwig & Erev, 2009): higher sensitivity to rare events in decisions from description. Comparison of judgment and decisions from experience reveals the coexistence of overestimation and underweighting of rare events (Barron & Yechiam, 2009). The current review suggests that both sets of differences are examples of the J/DM separation paradox: While separated studies of judgment and decision making reveal oversensitivity to rare events, without the separation, these processes often lead to the opposite bias. Our analysis shows that the J/DM paradox can be the product of the fact that the separation of judgment from decisions making requires an explicit presentation of the rare events, and this mere presentation increases the apparent weighting of these events. In addition, our analysis suggests that feedback diminishes the mere presentation effect, but does not guarantee increase in rational behavior. When people can rely on accurate feedback, the main deviations from rational judgment and decision making can be captured with the reliance on the small samples hypothesis.

Keywords

choice prediction competitionsBEASTlist effectamplification effectreaction to patternshot stove effect
Type
Chapter
Information
Sampling in Judgment and Decision Making , pp. 115 - 130
Publisher: Cambridge University Press
Print publication year: 2023

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