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Comparing the Calibration and Coherence of Numerical and Verbal Probability Judgments


Author Info

  • Thomas S. Wallsten

    (Department of Psychology, CB# 3270, Davie Hall, University of North Carolina, Chapel Hill, NC 27599-3270)

  • David V. Budescu

    (Department of Psychology, University of Illinois, Champaign, Illinois 61820)

  • Rami Zwick

    (Department of Marketing, The Pennsylvania State University, University Park, Pennsylvania 16802-9976)


Despite the common reliance on numerical probability estimates in decision research and decision analysis, there is considerable interest in the use of verbal probability expressions to communicate opinion. A method is proposed for obtaining and quantitatively evaluating verbal judgments in which each analyst uses a limited vocabulary that he or she has individually selected and scaled. An experiment compared this method to standard numerical responding under three different payoff conditions. Response mode and payoff never interacted. Probability scores and their components were virtually identical for the two response modes and for all payoff groups. Also, judgments of complementary events were essentially additive under all conditions. The two response modes differed in that the central response category was used more frequently in the numerical than the verbal case, while overconfidence was greater verbally than numerically. Response distributions and degrees of overconfidence were also affected by payoffs. Practical and theoretical implications are discussed.

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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 39 (1993)
Issue (Month): 2 (February)
Pages: 176-190

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Handle: RePEc:inm:ormnsc:v:39:y:1993:i:2:p:176-190

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Keywords: subjective probability; judgment; calibration; verbal probabilities; coherence; additivity;


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Cited by:
  1. David V. Budescu & Timothy R. Johnson, 2011. "A model-based approach for the analysis of the calibration of probability judgments," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(8), pages 857-869, December.
  2. Piercey, M. David, 2009. "Motivated reasoning and verbal vs. numerical probability assessment: Evidence from an accounting context," Organizational Behavior and Human Decision Processes, Elsevier, vol. 108(2), pages 330-341, March.
  3. Zimmer, Anja & Schade, Christian & Gr√ľndl, Helmut, 2009. "Is default risk acceptable when purchasing insurance? Experimental evidence for different probability representations, reasons for default, and framings," Journal of Economic Psychology, Elsevier, vol. 30(1), pages 11-23, February.
  4. Bender, Randall H., 1998. "Judgment and Response Processes across Two Knowledge Domains," Organizational Behavior and Human Decision Processes, Elsevier, vol. 75(3), pages 222-257, September.
  5. Nathaniel Wilcox, 2004. "Believing in Economic Theory: Sex, Lies, Evidence, Trust and Ideology," Working Papers 2004-06 Classification-, Department of Economics, University of Houston.
  6. Adam Harris & Adam Corner & Juemin Xu & Xiufang Du, 2013. "Lost in translation? Interpretations of the probability phrases used by the Intergovernmental Panel on Climate Change in China and the UK," Climatic Change, Springer, vol. 121(2), pages 415-425, November.
  7. Wallsten, Thomas S. & Diederich, Adele, 2001. "Understanding pooled subjective probability estimates," Mathematical Social Sciences, Elsevier, vol. 41(1), pages 1-18, January.
  8. Wallsten, Thomas S. & Gu, Hongbin, 2003. "Distinguishing choice and subjective probability estimation processes: Implications for theories of judgment and for cross-cultural comparisons," Organizational Behavior and Human Decision Processes, Elsevier, vol. 90(1), pages 111-123, January.
  9. Windschitl, Paul D., 2000. "The Binary Additivity of Subjective Probability Does not Indicate the Binary Complementarity of Perceived Certainty," Organizational Behavior and Human Decision Processes, Elsevier, vol. 81(2), pages 195-225, March.
  10. Richard Brody & John Coulter & Alireza Daneshfar, 2003. "Auditor Probability Judgments: Discounting Unspecified Possibilities," Theory and Decision, Springer, vol. 54(2), pages 85-104, March.


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