## Judgment Under Uncertainty: Heuristics and BiasesDaniel Kahneman, Stewart Paul Slovic, Paul Slovic, Amos Tversky Cambridge University Press, 30 apr 1982 - 555 pagine 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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### Indice

Judgment under uncertainty Heuristics and biases | 3 |

Belief in the law of small numbers | 23 |

Subjective probability A judgment of representativeness | 32 |

On the psychology of prediction | 48 |

Studies of representativeness | 69 |

Judgments of and by representativeness | 84 |

Popular induction Information is not necessarily informative | 101 |

Causal schemas in judgments under uncertainty | 117 |

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 |

521 | |

Index | 553 |

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Judgment under Uncertainty: Heuristics and Biases Daniel Kahneman,Paul Slovic,Amos Tversky Anteprima limitata - 1982 |

### Parole e frasi comuni

accuracy addicts Amos Tversky answer asked assessments attribution availability availability heuristic average base rate base-rate Bayes's theorem behavior beliefs bias biases biopsy calibration cancer causal clinical clinicians cognitive condition confidence consensus information correct correlation covariation Daniel Kahneman decision diagnostic distribution effect errors estimate evaluation evidence example expected experience experimental factors feedback Fischhoff fractiles frequency gambler's fallacy given grade heuristic hindsight bias hypothesis illusory correlation individual inferences interquartile range intuitive judged judgments Kahneman & Tversky less Lichtenstein likelihood linear models mammogram mammography Nisbett observed odds one's outcomes overconfidence patient person population posterior probability prediction presented prior probabilities probabilistic problem procedure proper linear model psychology question random reasoning regression relevant reported representativeness representativeness heuristic response retrieval Ross rule sample score significant similar situations Slovic social statistical subjective probability target task theory tion Tversky & Kahneman uncertainty validity variables