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How to Make Cognitive Illusions Disappear: Beyond “Heuristics and Biases”

How to Make Cognitive Illusions Disappear: Beyond “Heuristics and Biases” Most so-called “errors” in probabilistic reasoning are in fact not violations of probability theory. Examples of such “errors” include overconfidence bias, conjunction fallacy, and base-rate neglect. Researchers have relied on a very narrow normative view, and have ignored conceptual distinctions—e.g. single case versus relative frequency—fundamental to probability theory. By recognizing and using these distinctions, however, we can make apparently stable “errors” disappear, reappear, or even invert. I suggest what a reformed understanding of judgments under uncertainty might look like. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Review of Social Psychology Taylor & Francis

How to Make Cognitive Illusions Disappear: Beyond “Heuristics and Biases”

European Review of Social Psychology , Volume 2 (1): 33 – Jan 1, 1991

How to Make Cognitive Illusions Disappear: Beyond “Heuristics and Biases”

European Review of Social Psychology , Volume 2 (1): 33 – Jan 1, 1991

Abstract

Most so-called “errors” in probabilistic reasoning are in fact not violations of probability theory. Examples of such “errors” include overconfidence bias, conjunction fallacy, and base-rate neglect. Researchers have relied on a very narrow normative view, and have ignored conceptual distinctions—e.g. single case versus relative frequency—fundamental to probability theory. By recognizing and using these distinctions, however, we can make apparently stable “errors” disappear, reappear, or even invert. I suggest what a reformed understanding of judgments under uncertainty might look like.

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References (84)

Publisher
Taylor & Francis
Copyright
Copyright John Wiley & Sons Ltd.
ISSN
1479-277X
eISSN
1046-3283
DOI
10.1080/14792779143000033
Publisher site
See Article on Publisher Site

Abstract

Most so-called “errors” in probabilistic reasoning are in fact not violations of probability theory. Examples of such “errors” include overconfidence bias, conjunction fallacy, and base-rate neglect. Researchers have relied on a very narrow normative view, and have ignored conceptual distinctions—e.g. single case versus relative frequency—fundamental to probability theory. By recognizing and using these distinctions, however, we can make apparently stable “errors” disappear, reappear, or even invert. I suggest what a reformed understanding of judgments under uncertainty might look like.

Journal

European Review of Social PsychologyTaylor & Francis

Published: Jan 1, 1991

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