
Accession Number : ADA133418
Title : Ambiguity and Uncertainty in Probabilistic Inference.
Descriptive Note : Technical rept.,
Corporate Author : CHICAGO UNIV IL CENTER FOR DECISION RESEARCH
Personal Author(s) : Einhorn,Hillel J ; Hogarth,Robin M
PDF Url : ADA133418
Report Date : Sep 1983
Pagination or Media Count : 83
Abstract : Ambiguity results from having limited knowledge of the process that generates outcomes. It is argued that many realworld processes are perceived to be ambiguous; moreover, as Ellsberg demonstrated, this poses problems for theories of probability operationalized via choices amongst gambles. A descriptive model of how people make judgments under ambiguity in tasks where data come from a source of limited, but not exactly known reliability, is proposed. The model assumes an anchoringandadjustment process in which data provides the anchor, and adjustments are made for what might have been. The latter is modeled as the result of a mental simulation process that incorporates the unreliability of the source and one's attitude toward ambiguity in the circumstances. A twoparameter model of this process is shown to be consistent with: Keynes' idea of the weight of evidence, the nonadditivity of complementary probabilities, current psychological theories of risk, and Ellsberg's original paradox. The model is tested in four experiments at both the individual and group levels. In experiments 13, the model is shown to predict judgments quite well; in experiment 4, the inference model is shown to predict choices between gambles. The results and model are then discussed with respect to the importance of ambiguity in assessing perceived uncertainty; the use of cognitive strategies in judgments under ambiguity; the role of ambiguity in risky choice; and extensions of the model. (Author)
Descriptors : *Statistical inference, *Probability, *Ambiguity, Scenarios, Mathematical models, Tables(Data), Decision making, Predictions, Judgement(Psychology), Risk, Reliability, Parameters
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE