Coherence and correspondence in the psychological analysis of numerical predictions: How error-prone heuristics are replaced by ecologically valid heuristics

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Coherence and correspondence in the psychological analysis of numerical predictions: How error-prone heuristics are replaced by ecologically valid heuristics

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Yoav Ganzach

Abstract

Numerical predictions are of central interest for both coherence-based approaches to judgment and decisions --- the Heuristic and Biases (HB) program in particular --- and to correspondence-based approaches --- Social Judgment Theory (SJT). In this paper I examine the way these two approaches study numerical predictions by reviewing papers that use Cue Probability Learning (CPL), the central experimental paradigm for studying numerical predictions in the SJT tradition, while attempting to look for heuristics and biases. The theme underlying this review is that both bias-prone heuristics and adaptive heuristics govern subjects' predictions in CPL. When they have little experience to guide them, subjects fall prey to relying on bias-prone natural heuristics, such as representativeness and anchoring and adjustment, which are the only prediction strategies available to them. But, as they acquire experience with the prediction task, these heuristics are abandoned and replaced by ecologically valid heuristics.

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Article provided by Society for Judgment and Decision Making in its journal Judgment and Decision Making.

Volume (Year): 4 (2009)
Issue (Month): 2 (March)
Pages: 175-185
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Handle: RePEc:jdm:journl:v:4:y:2009:i:2:p:175-185

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References listed on IDEAS
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Jagacinski, Carolyn M., 1995. "Distinguishing Adding and Averaging Models in a Personnel Selection Task: When Missing Information Matters," Organizational Behavior and Human Decision Processes, Elsevier, vol. 61(1), pages 1-15, January. [Downloadable!] (restricted)
Tversky, Amos & Kahneman, Daniel, 1986. "Rational Choice and the Framing of Decisions," Journal of Business, University of Chicago Press, vol. 59(4), pages S251-78, October. [Downloadable!] (restricted)
Philip T. Dunwoody, 2009. "Theories of truth as assessment criteria in judgment and decision making," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(2), pages 116-125, March. [Downloadable!]

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This page was last updated on 2009-12-27.

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