Behavioral Decision Theory: A New Approach
This book discusses the well-known fallacies of behavioral decision theory. It shows that while an investigator is studying a fallacy, he or she may introduce without realizing it, one of the simple biases that are found in quantifying judgments. The work covers such fallacies as the apparent overconfidence that people show when they judge the probability of correctness of their answers to two-choice general knowledge questions using a one-sided rating scale; the apparent overconfidence in setting uncertainty bounds on unknown quantities when using the fractile method; the interactions between hindsight and memory; the belief that small samples are as reliable and as representative as are large samples; the conjunction fallacy for Linda and Bill; the causal conjunction fallacy; the regression fallacy in prediction; the neglect of the base rate in the Cab problem, in predicting professions, and in the Medical Diagnosis problem; the availability and simulation fallacies; the anchoring and adjustment biases; Prospect theory; and bias by frames. The aim of this book is to help readers to learn about the fallacies and to avoid them.
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Chapter 1 Outline of heuristics and biases
Chapter 2 Practical techniques
Chapter 3 Apparent overconfidence
Chapter 4 Hindsight bias
Chapter 5 Small sample fallacy
Chapter 6 Conjunction fallacy
Chapter 7 Regression fallacy
Chapter 8 Base rate neglect
Chapter 9 Availability and simulation fallacies
Chapter 10 Anchoring and adjustment biases
anchoring and adjustment apparent overconﬁdence Asymmetric transfer availability fallacy average base rate fallacy Bayes method biases binomial distribution boys chance Chapt Chapter choice choose Column commit the conjunction complex bias conﬁdence conjoint conjunction fallacy described diﬂerence disease eﬂect equal frequency bias estimate expected gain expected value fallacy for distributions ﬁgure ﬁrst Fischhoff Fischhoﬂ forecast fractiles frame gambler’s fallacy Gigerenzer heuristic hindsight bias increases independent probabilities inﬂuence interquartile investigation Israeli judged probability judgments Kahneman and Tversky knowledge questions Linda mean median memory normative rule Option outcome percent population Poulton predictions preferences probability of correctness probability rating Problem question proportion prospect theory psychology rank reduces reference magnitude regression fallacy reliable representative response contraction bias scores Sequence sequential contraction bias shows simple bias small sample fallacy statement sure loss surprise index Table task true values Tversky and Kahneman Tversky’s uncertainty bounds undergraduates unﬁlled University of Oregon unspeciﬁed backgrounds