Judgment under uncertainty : heuristics and biases / edited by Daniel Kahneman, Paul Slovic, Amos Tversky.
The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important social, medical, and political situations as well. Individual chapters discuss the representativeness and availability heuristics, problems in...
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| Language: | English |
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Cambridge ; New York :
Cambridge University Press,
[1982]
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MARC
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| 245 | 0 | 0 | |a Judgment under uncertainty : |b heuristics and biases / |c edited by Daniel Kahneman, Paul Slovic, Amos Tversky. |
| 264 | 1 | |a Cambridge ; |a New York : |b Cambridge University Press, |c [1982] | |
| 264 | 4 | |c ©1982 | |
| 300 | |a 1 online resource (xiii, 555 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a volume |b nc |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (pages 521-551) and index. | ||
| 505 | 0 | 0 | |t Judgment under uncertainty : heuristics and biases / |r Amos Tversky, |r Daniel Kahneman -- |t Belief in the law of small numbers / |r Amos Tversky, |r Daniel Kahneman -- |t Subjective probability : a judgment of representativeness / |r Daniel Kahneman, |r Amos Tversky -- |t On the psychology of prediction / |r Daniel Kahneman, |r Amos Tversky -- |t Studies of representativeness / |r Maya Bar-Hillel -- |t Judgments of and by representativeness / |r Amos Tversky, |r Daniel Kahneman -- |t Popular induction : information is not necessarily informative / |r Richard E. Nisbett [and others] -- |r Causal schemas in judgments under uncertainty / |r Amos Tversky, |r Daniel Kahneman -- |t Shortcomings in the attribution process : on the origins and maintenance of erroneous social assessments / |r Lee Ross, |r Craig A. Anderson -- |t Evidential impact of base rates / |r Amos Tversky, |r Daniel Kahneman -- |t Availability : a heuristic for judging frequency and probability / |r Amos Tversky, |r Daniel Kahneman -- |t Egocentric biases in availability and attribution / |r Michael Ross, |r Fiore Sicoly -- |t The availability bias in social perception and interaction / |r Shelley E. Taylor -- |t The simulation heuristic / |r Daniel Kahneman, |r Amos Tversky -- |t Informal covariation assessment : data-based versus theory-based judgments / |r Dennis L. Jennings, |r Teresa M. Amabile, |r Lee Ross -- |t The illusion of control / |r Ellen J. Langer -- |t Test results are what you think they are / |r Loren J. Chapman, |r Jean Chapman -- |t Probabilistic reasoning in clinical medicine : problems and opportunities / |r David M. Eddy -- |t Learning from experience and suboptimal rules in decision making / |r Hillel J. Einhorn -- |t Overconfidence in case-study judgments / |r Stuart Oskamp -- |t A progress report on the training of probability assessors / |r Marc Alpert, |r Howard Raiffa -- |t Calibration of probabilities : the state of the art to 1980 / |r Sarah Lichtenstein, |r Baruch Fischhoff, |r Lawrence D. Phillips -- |t For those condemned to study the past : heuristics and biases in hindsight / |r Baruch Fischhoff -- |t Evaluation of compound probabilities in sequential choice / |r John Cohen, |r E.I. Chesnick, |r D. Haran -- |t Conservatism in human information processing / |r Ward Edwards -- |t The best-guess hypothesis in multistage inference / |r Charles F. Gettys, |r Clinton Kelly III, |r Cameron R. Peterson -- |t Inferences of personal characteristics on the basis of information retrieved from one's memory / |r Yaacov Trope -- |t The robust beauty of improper linear models in decision making / |r Robyn M. Dawes -- |t The vitality of mythical numbers / |r Max Singer -- |t Intuitive prediction : biases and corrective procedures / |r Daniel Kahneman, |r Amos Tversky -- |t Debiasing / |r Baruch Fischhoff -- |t Improving inductive inference / |r Richard E. Nisbett [and others] -- |t Facts versus fears: understanding perceived risk / |r Paul Slovic, |r Baruch Fischhoff, |r Sarah Lichtenstein -- |t On the study of statistical intuitions / |r Daniel Kahneman, |r Amos Tversky -- |t Variants of uncertainty / |r Daniel Kahneman, |r Amos Tversky. |
| 520 | |a The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce, not only in laboratory experiments but in important social, medical, and political situations as well. Individual chapters discuss the representativeness and availability heuristics, problems in judging covariation and control, overconfidence, multistage inference, social perception, medical diagnosis, risk perception, and methods for correcting and improving judgments under uncertainty. About half of the chapters are edited versions of classic articles; the remaining chapters are newly written for this book. Most review multiple studies or entire subareas of research and application rather than describing single experimental studies. This book will be useful to a wide range of students and researchers, as well as to decision makers seeking to gain insight into their judgments and to improve them. | ||
| 588 | 0 | |a Online resource; title from digital title page (viewed on August 22, 2019). | |
| 546 | |a English. | ||
| 650 | 0 | |a Judgment. | |
| 650 | 0 | |a Heuristic. | |
| 650 | 7 | |a Heuristic |2 fast | |
| 650 | 7 | |a Judgment |2 fast | |
| 700 | 1 | |a Kahneman, Daniel, |d 1934-2024, |e editor. |1 https://id.oclc.org/worldcat/entity/E39PBJqfGfKBC4WrTKjQRXxRrq | |
| 700 | 1 | |a Slovic, Paul, |d 1938- |e editor. |1 https://id.oclc.org/worldcat/entity/E39PBJyxcDFRJCtg9jtYwrWxDq | |
| 700 | 1 | |a Tversky, Amos, |e editor. | |
| 758 | |i has work: |a Judgment under uncertainty (Work) |1 https://id.oclc.org/worldcat/entity/E39PCFQgXHjPQqRdgk7jXd3mMK |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |t Judgment under uncertainty. |d Cambridge ; New York : Cambridge University Press, ©1982 |z 0521240646 |w (DLC) 81010042 |w (OCoLC)7578020 |
| 856 | 4 | 0 | |u https://colorado.idm.oclc.org/login?url=https://doi.org/10.1017/CBO9780511809477 |z Full Text (via Cambridge) |
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