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What is a “likely” amount? Representative (modal) values are considered likely even when their probabilities are low

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  • Teigen, Karl Halvor
  • Juanchich, Marie
  • Løhre, Erik

Abstract

Research on verbal probabilities and standard scales issued by national and international authorities suggest that only events with probabilities above 60% should be labelled “likely”. We find, however, that when people apply this term to continuous variables, like expected costs, it describes the most likely (modal) outcome or interval, regardless of actual probabilities, which may be quite small. This was demonstrated in six studies in which lay participants (N = 2,228) were shown probability distributions from various domains and asked to generate or to select “likely” outcome intervals. Despite having numeric and graphically displayed information available, participants judged central, low-probability segments as “likely” (as opposed to equal or larger segments in the tails) and subsequently overestimated the chances of these outcomes. We conclude that high-probability interpretations of “likely” are only valid for binary outcomes but not for distributions of graded variables or multiple outcomes.

Suggested Citation

  • Teigen, Karl Halvor & Juanchich, Marie & Løhre, Erik, 2022. "What is a “likely” amount? Representative (modal) values are considered likely even when their probabilities are low," Organizational Behavior and Human Decision Processes, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:jobhdp:v:171:y:2022:i:c:s0749597822000504
    DOI: 10.1016/j.obhdp.2022.104166
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    1. repec:cup:judgdm:v:8:y:2013:i:3:p:345-364 is not listed on IDEAS
    2. Michael Theil, 2002. "The role of translations of verbal into numerical probability expressions in risk management: a meta-analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 5(2), pages 177-186, April.
    3. Riege, Anine H. & Teigen, Karl Halvor, 2013. "Additivity neglect in probability estimates: Effects of numeracy and response format," Organizational Behavior and Human Decision Processes, Elsevier, vol. 121(1), pages 41-52.
    4. Charness, Gary & Gneezy, Uri & Kuhn, Michael A., 2012. "Experimental methods: Between-subject and within-subject design," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 1-8.
    5. Teigen, Karl Halvor, 2001. "When Equal Chances = Good Chances: Verbal Probabilities and the Equiprobability Effect," Organizational Behavior and Human Decision Processes, Elsevier, vol. 85(1), pages 77-108, May.
    6. repec:cup:judgdm:v:10:y:2015:i:3:p:232-240 is not listed on IDEAS
    7. repec:cup:judgdm:v:16:y:2021:i:2:p:363-393 is not listed on IDEAS
    8. Erev, Ido & Cohen, Brent L., 1990. "Verbal versus numerical probabilities: Efficiency, biases, and the preference paradox," Organizational Behavior and Human Decision Processes, Elsevier, vol. 45(1), pages 1-18, February.
    9. van der Bles, Anne Marthe & van der Liden, Sander & Freeman, Alessandra L. J. & Mitchell, James & Galvao, Ana Beatriz & Spiegelhalter, David J., 2019. "Communicating uncertainty about facts, numbers, and science," EMF Research Papers 22, Economic Modelling and Forecasting Group.
    10. Isaac M. Lipkus & Greg Samsa & Barbara K. Rimer, 2001. "General Performance on a Numeracy Scale among Highly Educated Samples," Medical Decision Making, , vol. 21(1), pages 37-44, February.
    11. Yasmina Okan & Eva Janssen & Mirta Galesic & Erika A. Waters, 2019. "Using the Short Graph Literacy Scale to Predict Precursors of Health Behavior Change," Medical Decision Making, , vol. 39(3), pages 183-195, April.
    12. David V. Budescu & Han-Hui Por & Stephen B. Broomell & Michael Smithson, 2014. "The interpretation of IPCC probabilistic statements around the world," Nature Climate Change, Nature, vol. 4(6), pages 508-512, June.
    13. Bent Flyvbjerg, 2014. "What You Should Know About Megaprojects, and Why: An Overview," Papers 1409.0003, arXiv.org.
    14. repec:cup:judgdm:v:14:y:2019:i:6:p:683-695 is not listed on IDEAS
    15. Du, Ning & Budescu, David V. & Shelly, Marjorie K. & Omer, Thomas C., 2011. "The appeal of vague financial forecasts," Organizational Behavior and Human Decision Processes, Elsevier, vol. 114(2), pages 179-189, March.
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