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Judgment under Uncertainty

Heuristics and Biases

By: Amos Tversky (Editor), Paul Slovic (Editor), Daniel Kahneman (Editor)

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Paperback | 20 May 1982

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572 Pages

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22.6 x 15.0 x 2.7

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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.

Industry 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 "...an important and well-written book." Journal of the American Statistical Association "...a good collection of papers on an important topic." Quarterly Journal of Experimental Psychology "Clearly, this is an important book. Anyone who undertakes judgment and decision research should own it." Contemporary Psychology

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You Can Find This Book In

Non-Fiction Psychology Cognition & Cognitive Psychology

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Non-Fiction Psychology Cognition & Cognitive Psychology

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.

Judgment under Uncertainty

Heuristics and Biases

At a Glance

Paperback

Industry Reviews

Shipping

How to return your order

Defective items

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