Experiencing simulated outcomes
Robin Hogarth () and
Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra
Whereas much literature has documented difficulties in making probabilistic inferences, it has also emphasized the importance of task characteristics in determining judgmental accuracy. Noting that people exhibit remarkable efficiency in encoding frequency information sequentially, we construct tasks that exploit this ability by requiring people to experience the outcomes of sequentially simulated data. We report two experiments. The first involved seven well-known probabilistic inference tasks. Participants differed in statistical sophistication and answered with and without experience obtained through sequentially simulated outcomes in a design that permitted both between- and within-subject analyses. The second experiment involved interpreting the outcomes of a regression analysis when making inferences for investment decisions. In both experiments, even the statistically naïve make accurate probabilistic inferences after experiencing sequentially simulated outcomes and many prefer this presentation format. We conclude by discussing theoretical and practical implications.
Keywords: probabilistic reasoning; natural frequencies; experiential sampling; simulation., leex (search for similar items in EconPapers)
JEL-codes: C00 C11 C15 C91 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cbe, nep-exp and nep-neu
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Working Paper: Experiencing Simulated Outcomes (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:1224
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