Judgment Under Uncertainty
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패키지
북카드
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.
"...a good collection of papers on an important topic."Quarterly Journal of Experimental Psychology
"...an important and well-written book."Journal of the American Statistical Association
"Clearly, this is an important book. Anyone who undertakes judgment and decision research should own it." Contemporary Psychology
"The examples are lively, the style is engaging, and it is as entertaining as it is enlightening."Times Literary Supplement
"The papers chosen for this volume are an excellent collection, generally well-written and fascinating." Journal of Economic Literature
The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce.
Preface; Part I. Introduction: 1. Judgment under uncertainty: heuristics and biases Amos Tversky and Daniel Kahneman; Part II. Representativeness: 2. Belief in the law of small numbers Amos Tversky and Daniel Kahneman; 3. Subjective probability: a judgment of representativeness Daniel Kahneman and Amos Tversky; 4. On the psychology of presiction Daniel Kahneman and Amos Tversky; 5. Studies of representativeness Maya Bar-Hillel; 6. Judgments of and by representativeness Amos Tversky and Daniel Kahneman; Part III. Causality and Attribution: 7. Popular induction: information is not necessarily informative Richard E. Nisbett, Eugene Borgida, Rick Crandall and Harvey Reed; 8. Causal schemas in judgments under uncertainty Amos Tversky and Daniel Kahneman; 9. Shortcomings in the attribution process: on the origins and maintenance of erroneous social assessments Lee Ross and Craig A. Anderson; 10. Evidential impact of base rates Amos Tversky and Daniel Kahneman; Part IV. Availability: 11. Availability: a heuristic for judging frequency and probability Amos Tversky and Daniel Kahneman; 12. Egocentric biases in availability and attribution Michael Ross and Fiore Sicoly; 13. The availability bias in social perception and interaction Shelley E. Taylor; 14. The simulation heuristic Daniel Kahneman and Amos Tversky; Part V. Covariation and Control: 15. Informal covariation asssessment: data-based versus theory-based judgments Dennis L. Jennings, Teresa M. Amabile and Lee Ross; 16. The illusion of control Ellen J. Langer; 17. Test results are what you think they are Loren J. Chapman and Jean Chapman; 18. Probabilistic reasoning in clinical medicine: problems and opportunities David M. Eddy; 19. Learning from experience and suboptimal rules in decision making Hillel J. Einhorn; Part VI. Overconfidence: 20. Overconfidence in case-study judgments Stuart Oskamp; 21. A progress report on the training of probability assessors Marc Alpert and Howard Raiffa; 22. Calibration of probabilities: the state of the art to 1980 Sarah Lichtenstein, Baruch Fischhoff and Lawrence D. Phillips; 23. For those condemned to study the past: heuristics and biases in hindsight Baruch Fischhoff; Part VII. Multistage Evaluation: 24. Evaluation of compound probabilities in sequential choice John Cohen, E. I. Chesnick and D. Haran; 25. Conservatism in human information processing Ward Edwards; 26. The best-guess hypothesis in multistage inference Charles F. Gettys, Clinton Kelly III and Cameron R. Peterson; 27. Inferences of personal characteristics on the basis of information retrieved from one's memory Yaacov Trope; Part VIII. Corrective Procedures: 28. The robust beauty of improper linear models in decision making Robyn M. Dawes; 29. The vitality of mythical numbers Max Singer; 30. Intuitive prediction: biases and corrective procedures Daniel Kahneman and Amos Tversky; 31. Debiasing Baruch Fischhoff; 32. Improving inductive inference Richard E. Nesbett, David H. Krantz, Christopher Jepson and Geoffrey T. Fong; Part IX. Risk Perception: 33. Facts versus fears: understanding perceived risk Paul Slovic, Baruch Fischhoff and Sarah Lichtenstein; Part X. Postscript: 34. On the study of statistical intuitions Daniel Kahneman and Amos Tversky; 35. Variants of uncertainty Daniel Kahneman and Amos Tversky; References; Index.
작가정보
저자(글) Slovic,
목차
Preface Introduction Judgment under uncertainty: heuristics and biases Representativeness Belief in the law of small numbers Subjective probability: a judgment of representativeness On the psychology of presiction Studies of representativeness Judgments of and by representativeness Causality and Attribution Popular induction: information is not necessarily informative Causal schemas in judgments under uncertainty Shortcomings in the attribution process: on the origins and maintenance of erroneous social assessments Evidential impact of base rates Availability Availability: a heuristic for judging frequency and probability Egocentric biases in availability and attribution The availability bias in social perception and interaction The simulation heuristic Covariation and Control Informal covariation asssessment: data-based versus theory-based judgments The illusion of control Test results are what you think they are Loren Probabilistic reasoning in clinical medicine: problems and opportunities Learning from experience and suboptimal rules in decision making Overconfidence Overconfidence in case-study judgments A progress report on the training of probability assessors Calibration of probabilities: the state of the art to 1980 For those condemned to study the past: heuristics and biases in hindsight Multistage Evaluation Evaluation of compound probabilities in sequential choice Conservatism in human information processing The best-guess hypothesis in multistage inference Charles F. Gettys, Clinton Kelly III and Cameron Inferences of personal characteristics on the basis of information retrieved from oneG++s memory Corrective Procedures The robust beauty of improper linear models in decision making The vitality of mythical numbers Intuitive prediction: biases and corrective procedures Debiasing Baruch Fischhoff Improving inductive inference Risk Perception Facts versus fears: understanding perceived risk Postscript On the study of statistical intuitions Variants of uncertainty References Index Table of Contents provided by Publisher. All Rights Reserved.
기본정보
ISBN | 9780521284141 ( 0521284147 ) |
---|---|
발행(출시)일자 | 1982년 04월 30일 |
쪽수 | 544쪽 |
크기 |
152 * 226
* 25
mm
/ 771 g
|
총권수 | 1권 |
언어 | 영어 |
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