Article1991

Problem structuring aids for quantitative estimation

Donald G. MacGregor · Sarah Lichtenstein

32 citations0/0 files storedJournal of Behavioral Decision Making

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Decision-Making and Behavioral Economics Forecasting Techniques and Applications Clinical Reasoning and Diagnostic Skills

Abstract

Abstract An important part of decision making in many contexts is the estimation of numerical values for uncertain quantities, such as the projected costs of a development project or the number of people who use illegal drugs. In previous research, estimation accuracy for such quantities was found to be improved by algorithmic decomposition. The present study examines (a) the estimation performance of individuals using extended algorithms in which component estimates are produced by multiple methods, and (b) the effectiveness of algorithms produced by individuals after receiving training in algorithmic decomposition. The extended algorithm approach yielded some improvement in estimation performance. Subjects trained in algorithmic decomposition were able to produce algorithms, the effectiveness of which were dependent upon the presence of misinformation about components of the quantity to be estimated. The results are discussed in terms of the information processing demands imposed by detailed problem structuring.

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References

1974Judgment under Uncertainty: Heuristics and Biases 1973Availability: A heuristic for judging frequency and probability 1975The use of the decomposition principle in making judgments 1988Structuring knowledge retrieval: An analysis of decomposed quantitative judgments

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