Information Sampling and Adaptive Cognition
£36.99
- Editors:
- Klaus Fiedler, Ruprecht-Karls-Universität Heidelberg, Germany
- Peter Juslin, Uppsala Universitet, Sweden
- Date Published: March 2006
- availability: Available
- format: Paperback
- isbn: 9780521539333
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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.
Read more- Provides a genuine alternative to the heuristics-and-biases notion of the Kahneman-Tversky era that has dominated the field for decades
- Majority of researchers who have made important contributions to the sampling approach are all on board
- Judgment and decision making research has a profound impact on many disciplines, broadening audience and readership
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×Product details
- Date Published: March 2006
- format: Paperback
- isbn: 9780521539333
- length: 498 pages
- dimensions: 229 x 152 x 25 mm
- weight: 0.66kg
- contains: 61 b/w illus. 38 tables
- availability: Available
Table of Contents
Part I. Introduction:
1. Taking the interface between mind and environment seriously Klaus Fiedler and Peter Juslin
Part II. The Psychological Law of Large Number:
2. Good sampling, distorted views: the perception of variability Yakoov Kareev
3. Intuitive judgments about sample size Peter Sedlmeier
4. Risky prospects: when valued through a window of sampled experiences Ralph Hertwig, Greg Barron, Elke Weber and Ido Erev
5. Less is more in contingency assessment - or is it? Peter Juslin, Klaus Fiedler and Nick Chater
Part III. Biased and Unbiased Judgments from Biased Samples:
6. Subjective validity judgments as an index of sensitivity to sampling bias Peter Freytag and Klaus Fiedler
7. An analysis of structural availability biases and a brief study Robyn Dawes
8. Subjective confidence and the sampling of knowledge Joshua Klayman, Jack Soll, Peter Juslin, and Anders Winman
9. Contingency learning and biased group impressions Thorsten Meiser
10. Mental mechanisms: speculations on human causal learning and reasoning Nick Chater and Mike Oaksford
Part IV. What Information Contents Are Sampled?:
11. What's in a sample? A manual for building cognitive theories Gerd Gigerenzer
12. Assessing evidential support in an uncertain environment Chris M. White and Derek Koehler
13. Information sampling in group decision making: sampling biases and their consequences Andreas Mojzisch and Stefan Schulz-Hardt
14. Confidence in aggregation of opinions from multiple sources David Budescu, Adrian K. Rantilla, Tzur M. Kareliz and Hsiu Ting Yu
15. Self as a sample Joachim Krueger, Melissa Acevedo and Jordan Robbins
Part V. Vicissitudes of Sampling in the Researcher's Mind and Method:
16. Which world should be represented in representative design? Ulrich Hoffrage and Ralph Hertwig
17. 'I'm m/n confident that I'm correct': confidence in foresight and hindsight as a sampling probability Anders Winman and Peter Juslin
18. Natural sampling of stimuli in (artificial) grammar learning Fenna Poletiek
19. Is confidence in decisions related to feedback? Evidence - lack of evidence - from random samples of real-world behavior Robin Hogarth.
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