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Cited by 2,094Decision-Making and Behavioral EconomicsAcademic and Historical Perspectives in PsychologyEpistemology, Ethics, and Metaphysics

Confirmation, disconfirmation, and information in hypothesis testing

Klayman, Joshua, Ha, Young-won·1987·Psychological Review
DOI 10.1037/0033-295x.94.2.211
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Abstract

Strategies for hypothesis testing in scientific investigation and everyday reasoning have interested both psychologists and philosophers. A number of these scholars stress the importance of disconnrmation in reasoning and suggest that people are instead prone to a general deleterious "confirmation bias." In particular, it is suggested that people tend to test those cases that have the best chance of verifying current beliefs rather than those that have the best chance of falsifying them. We show, however; that many phenomena labeled "confirmation bias" are better understood in terms of a general positive test strategy. With this strategy, there is a tendency to test cases that are expected (or known) to have the property of interest rather than those expected (or known) to lack that property. This strategy is not equivalent to confirmation bias in the first sense; we show that the positive test strategy can be a very good heuristic for determining the truth or falsity of a hypothesis under realistic conditions. It can, however, lead to systematic errors or inefficiencies. The appropriateness of human hypothesis-testing strategies and prescriptions about optimal strategies must be understood in terms of the interaction between the strategy and the task at hand.

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  • A hypothesis can create bias as it often entails confirmation and other biases that generate evidence confirming that hypothesis while ignoring or dismissing conflicting evidence.

    “A hypothesis can create bias as it often entails confirmation and other biases that generate evidence, confirming that hypothesis while ignoring (or dismissing) conflicting evidence (Baldwin, 1993; Klayman & Ha, 1987; Wagenaar et al., 1993).”

    From Biased and biasing: the hidden bias cascade and bias snowball effects (2025) · cites this paper as Klayman & Ha, 1987

  • Selection of evidence based on relevance is related to confirmation bias in cognitive science, where learners have been observed to select data which they believe to be true (i.e. they fail to attempt to falsify their hypotheses).

    “In this sense,selection of evidence based on relevance is related to the confirmation bias in cognitive science, where learners have been observed to (arguably maladaptively) select data which they believe to be true (i.e. they fail to attempt to falsify their hypotheses) [133].”

    From Evolution and impact of bias in human and machine learning algorithm interaction (2020) · cites this paper as [133]

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Authors
Klayman, J., & Ha, Y.-W.
Affiliations
University of Chicago (US)
ORCID
Klayman, Joshua
Venue
Psychological Review
Publisher
American Psychological Association (APA)
Published
1987-04
Volume
94
Issue
2
Pages
211-228
ISSN
  • 0033-295X (ISSN-L)
  • 1939-1471
DOI
10.1037/0033-295x.94.2.211
OpenAlex
W2124371667
Cited by
2,094
References
107
Citations by year
2026: 28 · 2025: 35 · 2024: 53 · 2023: 51 · 2022: 44 · 2021: 71 · 2020: 60 · 2019: 60 · 2018: 70 · 2017: 72 · 2016: 47 · 2015: 57 · 2014: 53 · 2013: 61 · 2012: 71
FWCI
22.99
Type
journal article
Language
en
Open access
closed
Locations
Psychological Review (publishedVersion)
Funders
National Science Foundation (8309586)
Topics
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Social Sciences › Psychology › General Psychology › Academic and Historical Perspectives in Psychology
  • Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
Keywords
hypothesis testing, confirmation bias, disconfirmation, falsification, heuristics, scientific reasoning, everyday reasoning

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