How Do People Judge Conjunctive Probabilities from Experience? A Hierarchical Bayesian Model Comparison

Abstract

Judging whether multiple events will co-occur is an important aspect of everyday decision making; however, the underlying probabilities of occurrence are usually unknown and have to be inferred from experience. Using a rigorous, quantitative model comparison, we investigate how people judge the probabilities of multiple events to co-occur. In a computerized experiment, participants had to repeatedly choose between two pairs of conjunctive events (represented as two gambles). Participants had access to a small sample of information to estimate the probability that both events occur. A hierarchical Bayesian approach used for estimating the models’ parameters and for testing the models against each other showed that the plurality of participants were best described by the configural weighted average model. This model assumes that constituent probabilities are ranked by importance, weighted accordingly, and added up. The cognitive modeling approach provides an understanding of the cognitive processes underlying people's conjunctive probability judgments.


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