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Related Experiment Videos

Overconfidence in interval estimates.

Jack B Soll1, Joshua Klayman

  • 1INSEAD, Fontainebleau, France. jack.soll@insead.edu

Journal of Experimental Psychology. Learning, Memory, and Cognition
|February 26, 2004
PubMed
Summary
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Judges were overconfident when estimating numerical ranges, with correct answers falling within their stated confidence intervals far less than expected. This overconfidence stems from systematically setting intervals too narrow, unlike binary choices.

Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Judgment and Decision Making

Background:

  • Overconfidence in judgment is a well-documented phenomenon.
  • Previous research indicates overconfidence can vary based on the task format.

Purpose of the Study:

  • To investigate the extent of overconfidence in numerical interval estimation.
  • To identify the primary causes of overconfidence in subjective interval estimates.
  • To explore factors influencing the degree of overconfidence.

Main Methods:

  • Participants provided numerical interval estimates with specified confidence levels (e.g., 80% sure).
  • The actual occurrence of the correct answer within the estimated intervals was recorded.
  • Comparisons were made between interval estimates and binary choice judgments.

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Main Results:

  • Judges exhibited significant overconfidence, with actual coverage falling substantially below the stated confidence level.
  • Subjective intervals were often too narrow, sometimes only 40% of the necessary width for calibration.
  • Overconfidence varied based on elicitation methods, domains, and judge's gender.

Conclusions:

  • Systematic underestimation of interval width is a primary driver of overconfidence in numerical estimation.
  • The way confidence intervals are elicited significantly impacts judgment accuracy.
  • Psychological mechanisms underlying these overconfidence patterns warrant further investigation.