Judgment under uncertainty : heuristics and biases
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Judgment under uncertainty : heuristics and biases
Cambridge University Press, 1982
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Judgement under uncertainty : heuristics and biases
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Note
Bibliography: p. [521]-551
Includes index
Description and Table of Contents
Description
Table of Contents
- 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.
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