Judgment Under Uncertainty Heuristics and Biases 1st Edition by Daniel Kahneman, Paul Slovic, Amos Tversky ISBN 1107266076 9781107266070

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ISBN 10: 1107266076
ISBN 13: 978-1107266070
Author: Daniel Kahneman, Paul Slovic, Amos Tversky
Judgment Under Uncertainty: Heuristics and Biases 1st Edition: 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.

 

Judgment Under Uncertainty: Heuristics and Biases 1st Table of contents:

Part I: Introduction
1 Judgment under uncertainty: Heuristics and biases

• Representativeness
• Insensitivity to prior probability of outcomes
• Insensitivity to sample size
• Misconceptions of chance
• Insensitivity to predictability
• The illusion of validity
• Misconceptions of regression
• Availability
• Adjustment and anchoring
• Discussion
• Summary

Part II: Representativeness
2 Belief in the law of small numbers
3 Subjective probability: A judgment of representativeness
4 On the psychology of prediction
5 Studies of representativeness
6 Judgments of and by representativeness

Part III: Causality and attribution
7 Popular induction: Information is not necessarily informative
8 Causal schemas in judgments under uncertainty
9 Shortcomings in the attribution process
10 Evidential impact of base rates

Part IV: Availability
11 Availability: A heuristic for judging frequency and probability
12 Egocentric biases in availability and attribution
13 The availability bias in social perception and interaction
14 The simulation heuristic

Part V: Covariation and control
15 Informal covariation assessment: Data-based versus theory-based judgments
16 The illusion of control
17 Test results are what you think they are
18 Probabilistic reasoning in clinical medicine: Problems and opportunities
19 Learning from experience and suboptimal rules in decision making

Part VI: Overconfidence
20 Overconfidence in case-study judgments
21 A progress report on the training of probability assessors
22 Calibration of probabilities: The state of the art to 1980
23 For those condemned to study the past: Heuristics and biases in hindsight

Part VII: Multistage evaluation
24 Evaluation of compound probabilities in sequential choice
25 Conservatism in human information processing
26 The best-guess hypothesis in multistage inference
27 Inferences of personal characteristics on the basis of information retrieved from one’s memory

Part VIII: Corrective procedures
28 The robust beauty of improper linear models in decision making
29 The vitality of mythical numbers
30 Intuitive prediction: Biases and corrective procedures
31 Debiasing
32 Improving inductive inference

Part IX: Risk perception
33 Facts versus fears: Understanding perceived risk

Part X: Postscript
34 On the study of statistical intuitions
35 Variants of uncertainty

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