About this product

Product Identifiers

PublisherCambridge University Press

ISBN-100521284147

ISBN-139780521284141

eBay Product ID (ePID)950515

Product Key Features

Number of Pages544 Pages

Publication NameJudgment under Uncertainty : Heuristics and Biases

LanguageEnglish

Publication Year1982

SubjectDiscrimination & Race Relations, Cognitive Psychology & Cognition

TypeTextbook

AuthorPaul Slovic

Subject AreaSocial Science, Psychology

FormatTrade Paperback

Dimensions

Item Height1.1 in

Item Weight28.7 Oz

Item Length9 in

Item Width5.9 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN81-010042

Reviews"The papers chosen for this volume are an excellent collection, generally well-written and fascinating." Journal of Economic Literature, "The examples are lively, the style is engaging, and it is as entertaining as it is enlightening." Times Literary Supplement, "...a good collection of papers on an important topic." Quarterly Journal of Experimental Psychology, "The examples are lively, the style is engaging, and it is as entertaining as it is enlightening."Times Literary Supplement, "Clearly, this is an important book. Anyone who undertakes judgment and decision research should own it." Contemporary Psychology

Dewey Edition19

IllustratedYes

Dewey Decimal153.4/6

Table Of ContentPreface; 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.

SynopsisThe 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., 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.

LC Classification NumberBF441 .J8 1982