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Between ignorance and truth: Partition dependence and learning in judgment under uncertainty
Kelly E See1, Craig R Fox, Yuval S Rottenstreich
1Department of Management and Organizations, Stern School of Business, New York University, New York, NY 10012, USA. ksee@stern.nyu.edu
Journal of Experimental Psychology. Learning, Memory, and Cognition
|November 8, 2006
Summary
People
Area of Science:
- Cognitive psychology and decision-making research.
- Investigating human probability judgment and cognitive biases.
Background:
- Humans often estimate probabilities based on observed frequencies.
- Cognitive biases can influence probability judgments, especially under uncertainty.
Purpose of the Study:
- To examine how frequency information and prior knowledge interact in probability estimation.
- To understand the influence of subjective partitioning of the state space on judgments.
Main Methods:
- Participants viewed multiattribute objects with varying frequencies.
- Judgments of attribute likelihood were collected and analyzed.
- Experimental conditions manipulated the salience of ignorance priors and confidence.
Main Results:
- Judged probabilities were a blend of observed attribute frequency and ignorance priors.
- Judgments were dependent on how participants subjectively divided the possibilities.
- Confidence reduced bias, while salient ignorance priors increased insensitivity to confidence.
Conclusions:
- Human probability judgments are influenced by both data and prior beliefs about uncertainty.
- Subjective organization of information (partition dependence) significantly impacts decision-making.
- Confidence and prior salience modulate the impact of cognitive biases in probability estimation.
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