A model of conditional probability judgment

Abstract

A standard view in cognitive psychology is that people estimate probabilities using heuristics that do not follow probability theory. We describe a model of probability estimation where people do follow probability theory in estimation, but are subject to random error or noise. This model predicts that people's conditional probability estimates will agree closely with probability theory for certain noise-cancelling expressions, but deviate from probability theory for other expressions. We describe an experiment which strongly confirms these predictions, suggesting that people estimate conditional probabilities in a way that follows standard probability theory, but is subject to the biasing effects of random noise.


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