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Probability judgment in three-category classification learning.

D J Koehler1

  • 1Department of Psychology, University of Waterloo, Ontario, Canada. dkoehler@watarts.uwaterloo.ca

Journal of Experimental Psychology. Learning, Memory, and Cognition
|February 22, 2000
PubMed
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People consistently make subadditive probability judgments, where sums exceed 1, violating probability theory. This study found cue conflict influences this bias, which can be modeled by support theory.

Area of Science:

  • Cognitive psychology
  • Decision science
  • Probability theory

Background:

  • Probability theory dictates that the sum of probabilities for mutually exclusive events should not exceed 1.
  • However, individuals often exhibit subadditive probability judgments, summing to more than 1 when assessing multiple hypotheses.
  • Understanding the evidential influences on this cognitive bias is crucial for accurate judgment and decision-making.

Purpose of the Study:

  • To investigate the phenomenon of subadditive probability judgments in humans.
  • To examine the influence of cue conflict, cue frequency, and cue redundancy on subadditivity.
  • To test the applicability of support theory in modeling these judgments.

Main Methods:

  • Conducted 5 experiments employing a classification-learning task.

Related Experiment Videos

  • Participants provided probability and frequency judgments for mutually exclusive hypotheses.
  • Manipulated evidential influences such as cue conflict, frequency, and redundancy.

    • Main Results:

    • Systematic subadditivity in probability and frequency judgments was observed, even with experimentally learned cues.
    • Cue conflict reliably increased the degree of subadditivity.
    • A linear-discounting model within support theory effectively described the observed judgments.

    Conclusions:

    • Subadditive probability judgments are a robust finding in human cognition, extending to frequency assessments.
    • Evidential factors, particularly cue conflict, significantly contribute to this judgmental bias.
    • Support theory provides a viable framework for understanding and modeling subadditive probability judgments.