Information Sampling and Adaptive Cognition

doi:10.1017/CBO9780511614576

A 'sample' is not only a concept from statistics that has penetrated common sense but also a metaphor that has inspired much research and theorizing in current psychology. The sampling approach emphasizes the selectivity and the biases that are inherent in the samples of information input with which judges and decision makers are fed. As environmental samples are rarely random, or representative of the world as a whole, decision making calls for censorship and critical evaluation of the data given. However, even the most intelligent decision makers tend to behave like 'näive intuitive statisticians': quite sensitive to the data given but uncritical concerning the source of the data. Thus, the vicissitudes of sampling information in the environment together with the failure to monitor and control sampling effects adequately provide a key to re-interpreting findings obtained in the last two decades of research on judgment and decision making.

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Contents

Frontmatter
pp i-iv
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Contents
pp v-vi
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List of Contributors
pp vii-viii
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PART I - INTRODUCTION
pp 1-2
- By Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany, Peter Juslin, Professor of Psychology, University of Uppsala, Sweden
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1 - Taking the Interface between Mind and Environment Seriously
pp 3-30
- By Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany, Peter Juslin, Professor of Psychology, University of Uppsala, Sweden
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PART II - THE PSYCHOLOGICAL LAW OF LARGE NUMBERS
pp 31-32
- By Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany, Peter Juslin, Professor of Psychology, University of Uppsala, Sweden
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2 - Good Sampling, Distorted Views: The Perception of Variability
pp 33-52
- By Yaakov Kareev, The Hebrew University of Jerusalem
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3 - Intuitive Judgments about Sample Size
pp 53-71
- By Peter Sedlmeier, Chemnitz University of Technology, Germany
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4 - The Role of Information Sampling in Risky Choice
pp 72-91
- By Ralph Hertwig, University of Basel, Switzerland, Greg Barron, Harvard Business School, Elke U. Weber, Columbia University, Ido Erev, Technion, Israel Institute of Technology
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5 - Less Is More in Covariation Detection – Or Is It?
pp 92-124
- By Peter Juslin, University of Uppsala, Sweden, Klaus Fiedler, University of Heidelberg, Germany, Nick Chater, University Collage, London
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PART III - BIASED AND UNBIASED JUDGMENTS FROM BIASED SAMPLES
pp 125-126
- By Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany, Peter Juslin, Professor of Psychology, University of Uppsala, Sweden
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6 - Subjective Validity Judgments as an Index of Sensitivity to Sampling Bias
pp 127-146
- By Peter Freytag, University of Heidelberg, Germany, Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany
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7 - An Analysis of Structural Availability Biases, and a Brief Study
pp 147-152
- By Robyn M. Dawes, Carnegie Mellon University
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8 - Subjective Confidence and the Sampling of Knowledge
pp 153-182
- By Joshua Klayman, University of Chicago Graduate School of Business, Jack B. Soll, INSEAD Business School, France, Peter Juslin, Professor of Psychology, Uppsala University in Sweden, Anders Winman, Uppsala University, Sweden
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9 - Contingency Learning and Biased Group Impressions
pp 183-209
- By Thorsten Meiser, University Of Jena, Germany
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10 - Mental Mechanisms: Speculations on Human Causal Learning and Reasoning
pp 210-236
- By Nick Chater, University College, London, Mike Oaksford, University of London
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PART IV - WHAT INFORMATION CONTENTS ARE SAMPLED?
pp 237-238
- By Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany, Peter Juslin, Professor of Psychology, University of Uppsala, Sweden
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11 - What's in a Sample? A Manual for Building Cognitive Theories
pp 239-260
- By Gerd Gigerenzer, Max Planck Institute, Germany
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12 - Assessing Evidential Support in Uncertain Environments
pp 261-298
- By Chris M. White, Université de Lausanne, Switzerland, Derek J. Koehler, University of Waterloo, Canada
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13 - Information Sampling in Group Decision Making: Sampling Biases and Their Consequences
pp 299-326
- By Andreas Mojzisch, Universität Göttingen, Germany, Stefan Schulz-Hardt, Universität München, Germany
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14 - Confidence in Aggregation of Opinions from Multiple Sources
pp 327-352
- By David V. Budescu, University of Illinois
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15 - Self as Sample
pp 353-378
- By Joachim I. Krueger, Brown University, Melissa Acevedo, Brown University, Jordan M. Robbins, Brown University
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PART V - VICISSITUDES OF SAMPLING IN THE RESEARCHER'S MIND AND METHOD
pp 379-380
- By Klaus Fiedler, Professor of Psychology, University of Heidelberg in Germany, Peter Juslin, Professor of Psychology, University of Uppsala, Sweden
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16 - Which World Should Be Represented in Representative Design?
pp 381-408
- By Ulrich Hoffrage, Max Planck Institute, Germany, Ralph Hertwig, University of Basel, Switzerland
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17 - “I'm m/n Confident That I'm Correct”: Confidence in Foresight and Hindsight as a Sampling Probability
pp 409-439
- By Anders Winman, Uppsala University, Sweden, Peter Juslin, Professor of Psychology, Uppsala University in Sweden
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18 - Natural Sampling of Stimuli in (Artificial) Grammar Learning
pp 440-455
- By Fenna H. Poletiek, Leiden University, The Netherlands
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19 - Is Confidence in Decisions Related to Feedback? Evidence from Random Samples of Real-World Behavior
pp 456-484
- By Robin M. Hogarth, Universitat Pompeu Fabra, Spain
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Index
pp 485-488
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