Judgment Under Uncertainty: Heuristics and Biases

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Cambridge University Press, 30 avr. 1982 - 555 pages
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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.
 

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Table des matières

Overconfidence in casestudy judgments
287
A progress report on the training of probability assessors
294
Calibration of probabilities The state of the art to 1980
306
For those condemned to study the past Heuristics and biases in hindsight
335
Evaluation of compound probabilities in sequential choice
355
Conservatism in human information processing
359
The bestguess hypothesis in multistage inference
370
Inferences of personal characteristics on the basis of information retrieved from ones memory
378

Shortcomings in the attribution process On the origins and maintenance of erroneous social assessments
129
Evidential impact of base rates
153
Availability A heuristic for judging frequency and probability
163
Egocentric biases in availability and attribution
179
The availability bias in social perception and interaction
190
The simulation heuristic
201
Informal covariation assessment Databased versus theorybased judgments
211
The illusion of control
231
Test results are what you think they are
239
Probabilistic reasoning in clinical medicine Problems and opportunities
249
Learning from experience and suboptimal rules in decision making
268
The robust beauty of improper linear models in decision making
391
The vitality of mythical numbers
408
Intuitive prediction Biases and corrective procedures
414
Debiasing
422
Improving inductive inference
445
Facts versus fears Understanding perceived risk
463
On the study of statistical intuitions
493
Variants of uncertainty
509
References
521
Index
553
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Page 92 - Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.
Page 44 - A certain town is served by two hospitals. In the larger hospital about 45 babies are born each day, and in the smaller hospital about 15 babies are born each day. As you know, about 50 percent of all babies are boys.
Page 12 - Biases due to the Effectiveness of a Search Set Suppose one samples a word (of three letters or more) at random from an English text. Is it more likely that the word starts with r or that r is the third letter? People approach this problem by recalling words that begin with r (road) and words that have r in the third position (car) and assess the relative frequency by the ease with which words of the two types come to mind. Because it is much easier to search for words by their first letter than...
Page 33 - A person who follows this heuristic evaluates the probability of an uncertain event, or a sample, by the degree to which it is (i) similar in essential properties to its parent population; and (ii) reflects the salient features of the process by which it is generated.
Page 16 - ... particular day, in the form of a probability distribution. Such a distribution is usually constructed by asking the person to select values of the quantity that correspond to specified percentiles of his subjective probability distribution. For example, the judge may be asked to select a number...
Page 6 - In the larger hospital about 45 babies are born each day, and in the smaller hospital about 15 babies are born each day. As you know, about 50 percent of all babies are boys. However, the exact percentage varies from day to day. Sometimes it may be higher than 50 percent, sometimes lower. For a period of 1 year, each hospital recorded the days on which more than 60 percent of the babies born were boys.
Page 10 - Galton more than 100 years ago. In the normal course of life, one encounters many instances of regression toward the mean, in the comparison of the height of fathers and sons, of the intelligence of husbands and wives, or of the performance of individuals on consecutive examinations. Nevertheless, people do not develop correct intuitions about this phenomenon. First, they do not expect regression in many contexts where it is bound to occur. Second, when they recognize the occurrence of regression,...
Page 465 - A major limitation to human ability to use improved flood hazard information is a basic reliance on experience. Men on flood plains appear to be very much prisoners of their experience .... Recently experienced floods appear to set an upward bound to the size of loss with which managers believe they ought to be concerned (Kates, 1962: 140) . Kates attributes much of the difficulty in improving flood control to the "inability of individuals to conceptualize floods that have never occurred
Page 6 - However, the exact percentage varies from day to day. Sometimes it may be higher than 50 percent, sometimes lower. For a period of 1 year, each hospital recorded the days on which more than 60 percent of the babies born were boys. Which hospital do you think recorded more such days? The larger hospital (21) The smaller hospital (21) About the same (that is, within 5 percent of each other) (53) The values in parentheses are the number of undergraduate students who chose each answer. Most subjects...
Page 56 - Dick is a 30-year-old man. He is married with no children. A man of high ability and high motivation, he promises to be quite successful in his field. He is well liked by his colleagues.

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À propos de l'auteur (1982)

Daniel Kahneman received the 2002 Nobel Prize in Economic Sciences for his pioneering work with Amos Tversky on decision-making.

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