Causal model and sampling approaches to reducing base rate neglect

Abstract

Two studies examined how sampling of base rate information and causal explanation of false positives facilitate intuitive probability judgments. Experiment 1a varied these two manipulations factorially. Each had an additive effect on reducing base rate neglect and increasing choice of the normatively correct solution. Experiment 1b showed that description of relevant distributional information produced similar facilitation to sequential sampling. These results indicate that causal and sampling approaches impact on different components of probability judgment.


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