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100%: KAHNEMAN, DANIEL ; SLOVIC, PAUL ; & TVERSKY, AMOS: Judgment under Uncertainty: Heuristics and Biases (ISBN: 9781225245957) in Englisch.
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100%: Sous la direction de: Daniel Kahneman, Sous la direction de: Paul Slovic, Sous la direction de: Amos Tversky: Judgment under Uncertainty: Heuristics and Biases (ISBN: 9780521240642) 1982, Cambridge University Press, Erstausgabe, in Englisch, Broschiert.Nur diese Ausgabe anzeigen…
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Judgment Under Uncertainty
EN NWISBN: 9780521284141 bzw. 0521284147, in Englisch, Cambridge University Press, Vereinigtes Königreich Großbritannien und Nordirland, neu.
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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.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.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.The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce.
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.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.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.The thirty-five chapters in this book describe various judgmental heuristics and the biases they produce.
2
Judgment under Uncertainty: Heuristics and Biases
ENISBN: 1225245958 bzw. 9781225245957, in Englisch.
Lieferung aus: Dänemark, zzgl. Versandkosten.
Von Händler/Antiquariat, Expatriate Bookshop of Denmark [expat].
Cambridge, Cambridge University Press, (2005). 21st printing, Orig.wrappers. 23x15cm, xiii,555 pp, PAPERBACK.. Minor rubbing. VG. ¶ 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" - Publisher's description.
Von Händler/Antiquariat, Expatriate Bookshop of Denmark [expat].
Cambridge, Cambridge University Press, (2005). 21st printing, Orig.wrappers. 23x15cm, xiii,555 pp, PAPERBACK.. Minor rubbing. VG. ¶ 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" - Publisher's description.
3
Judgment Under Uncertainty (1982)
~EN PB NWISBN: 9780521284141 bzw. 0521284147, vermutlich in Englisch, Cambridge University Press, Taschenbuch, neu.
Lieferung aus: Deutschland, Sofort lieferbar.
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. Taschenbuch, 01.05.1982.
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. Taschenbuch, 01.05.1982.
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Judgment under Uncertainty: Heuristics and Biases (1982)
EN HCISBN: 9780521240642 bzw. 0521240646, in Englisch, Cambridge University Press, gebundenes Buch.
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Judgment under Uncertainty
~EN PB NWISBN: 9780521284141 bzw. 0521284147, vermutlich in Englisch, Cambridge University Press, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Judgment under Uncertainty: 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. Englisch, Taschenbuch.
Judgment under Uncertainty: 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. Englisch, Taschenbuch.
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Judgment under Uncertainty
~EN NWISBN: 9780521284141 bzw. 0521284147, vermutlich in Englisch, Cambridge University Press, neu.
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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.
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.
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