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Cognitive Processes and the Assessment of Subjective Probability Distributions

Hogarth, Robin M.·1975·Journal of the American Statistical Association

Abstract

This article considers the implications of recent research on judgmental processes for the assessment of subjective probability distributions. It is argued that since man is a selective, sequential information processing system with limited capacity, he is ill-suited for assessing probability distributions. Various studies attesting to man's difficulties in acting as an “intuitive statistician” are summarized in support of this contention. The importance of task characteristics on judgmental performance is also emphasized. A critical survey of the probability assessment literature is provided and organized around five topics: (1) the “meaningfulness” of probability assessments; (2) methods of eliciting distributions; (3) feedback and evaluation of assessors; (4) differential ability of groups of assessors and (5) the problems of eliciting a single distribution from a group of assessors. Conclusions from the analysis with respect to future work include the need to capitalize on cognitive simplification mechanisms; making assessors aware of both human limitations and the effects of task characteristics; and emphasizing feedback concerning the nature of the task at hand.

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Metadata

Authors
Hogarth, R. M.
Venue
Journal of the American Statistical Association
Published
1975-06
Volume
70
Issue
350
Pages
271-289
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W2076441302
Cited by
479
References
9
FWCI
16.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Cognitive Processes and the Assessment of Subjective Probability Distributions. https://app.cochat.ai/papers/10.1080/01621459.1975.10479858
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Hogarth, R. M. (1975). Cognitive Processes and the Assessment of Subjective Probability Distributions. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1975.10479858

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.