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Subjective Probability: A Judgment of Representativeness

  • Daniel Kahneman
  • Amos Tversky
Chapter
Part of the Theory and Decision Library book series (TDLU, volume 8)

Abstract

This paper explores a heuristic — representativeness — according to which the subjective probability of an event, or a sample, is determined by the degree to which it: (i) is similar in essential characteristics to its parent population; and (ii) reflects the salient features of the process by which it is generated. This heuristic is explicated in a series of empirical examples demonstrating predictable and systematic errors in the evaluation of uncertain events. In particular, since sample size does not represent any property of the population, it is expected to have little or no effect on judgment of likelihood. This prediction is confirmed in studies showing that subjective sampling distributions and posterior probability judgments are determined by the most salient characteristic of the sample (e.g., proportion, mean) without regard to the size of the sample. The present heuristic approach is contrasted with the normative (Bayesian) approach to the analysis of the judgment of uncertainty.

Keywords

Posterior Probability Subjective Probability Parent Population Sample Ratio Sample Difference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Bibliography

  1. Alberoni, F., ‘Contribution to the Study of Subjective Probability’, Part I. Journal of General Psychology, 66 (1962) 241–264.CrossRefGoogle Scholar
  2. Beach, L.R., Wise, J.A., and Barclay, S., ‘Sample Proportion and Subjective Probability Revisions’. Organizational Behavior and Human Performance 5 (1970), 183–190.CrossRefGoogle Scholar
  3. Cohen, J.,‘The Statistical Power of Abnormal-Social Psychological Research’, Journal of Abnormal and Sockal Psychology 65 (1962), 145–153.CrossRefGoogle Scholar
  4. Cohen, J., and Hansel, C.E.M., Risk and Gambling, Philosophical Library, New York. 1956.Google Scholar
  5. Edwards, W., ‘Conservatism in Human Information Processing’, in B. Kleinmuntz (ed.). Formal Representation of Human Judgment, Wiley, New York, 1968, pp 17–52.Google Scholar
  6. Extes, W.K., ‘Probability Learning’, in A W Melton (ed.), Categories of Human Learning, Academic Press, New York, 1964, pp. 89–128.Google Scholar
  7. Feller, W., An Introduction to Probability Theory and Its Applications ( 3rd ed. ). Vol. I, Wiley, New York. 1968.Google Scholar
  8. Garner, W.R., ‘Good Patterns Have Few Alternatives’, American Scientist 58 (1970), 34–43.Google Scholar
  9. Glanzer, M., and Clark, W.H., ‘Accuracy of Perceptual Recall: An Analysis of Orgarnization’. Journal of Verbal Learning and Verbal Behavior 1 (1963), 289–299.CrossRefGoogle Scholar
  10. Goodfellow, L.D., ‘A Psychological Interpretation of the Results of the Zenith Radio Experiments in Telepathy’. Journal of Experimental Psychology 23 (1938). 601–632.CrossRefGoogle Scholar
  11. Johnson-Laird, P.N., and Wason, P.C., ‘A Theoretical Analysts of Insight Intoa Reasoning Task’, Cognitive Psychology, 1 (1970), 134–148CrossRefGoogle Scholar
  12. Jones, M.R., ‘From Probability Learning to Sequential Processing: A Critical Review’. Psychological Bulletin 76 (1971), 153–185.CrossRefGoogle Scholar
  13. Peterson, C.R., and Beach, L.R., ‘Man as an Intuitive Statistician’. Psychological Bulletin 68 (1967), 29–46.CrossRefGoogle Scholar
  14. Peterson, C.R., Schneider, R.J., and Miller, A J., ‘Sample Size and the Revision of Subjective Probabilities’. Journal of Experimental Psychology 69 (1965), 522–527.CrossRefGoogle Scholar
  15. Pitz, G F., ‘Sample Size, Likelihood, and Confidence in a Decision’, Psychcmomic Science 8 (1967), 257–258.Google Scholar
  16. Pitz, G. F., Downing, L., and Remhold, H,‘Sequential Effects in the Revision of Subjective Probabilities’, Canadian Journal of Psychology 21 (1967), 381–393.CrossRefGoogle Scholar
  17. Rapoport, A., and Wallsten, T.S., ‘Individual Decision Behavior’. (Vol. 23) in Annual Review of Psychology, Annual Reviews, Palo Alto, 1972, pp. 131–176.Google Scholar
  18. Shanteau, J.C., ‘An Additive Model for Decision-Making’, Journal of Experimental Psychology 85 (1970), 181–191.CrossRefGoogle Scholar
  19. Slovic, P, and Lichtenstein, S., ‘Comparison of Bayesian and Regression Approaches to the Study of Information in Judgment’, Organizational Behavior and Human Performance 6 (1971). 648–744.CrossRefGoogle Scholar
  20. Tune, G.S., ‘Response Preferences: A Review of Some Relevant Literature’. Psychological Bulletin 61 (1964), 280–302.CrossRefGoogle Scholar
  21. Tversky, A., and Kahneman, D., ‘Belief in the Law of Small Numbers’. Psychological Bulletin 76 (1971), 105–110.CrossRefGoogle Scholar
  22. Tversky, A. and Kahneman, D., ‘Availability: A Heunvtic for Judging Frequency and Probability’, Cognitive Psychology 5 (1973). 207–232.CrossRefGoogle Scholar
  23. Vitz, P.C., and Todd, T.C., ‘A Coded Element Model of the Perceptual Processing of Sequential Stimuli’. Psychological Review, 76 (1969), 433–449.CrossRefGoogle Scholar
  24. Vlek, C., ‘The Use of Probabilistic Information in Decision-Making’, Psychological Institute Report No. 009-65, University of Leiden, The Netherlands, 1965.Google Scholar
  25. Wagenaar, W.A., ‘Subjective Randomnew and the Capacity to Generate Information’, in A.F. Sanders (Ed.), Attention and Performance III, Acta Ptychologica, 33 (1970), 233–242.Google Scholar

Copyright information

© Academic Press 1972

Authors and Affiliations

  • Daniel Kahneman
    • 1
  • Amos Tversky
    • 1
  1. 1.The Hebrew UniversityJerusalemIsrael

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