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A theory of learning to infer
[article]
2019
biorxiv/medrxiv
pre-print
Bayesian theories of cognition assume that people can integrate probabilities rationally. However, several empirical findings contradict this proposition: human probabilistic inferences are prone to systematic deviations from optimality. Puzzlingly, these deviations sometimes go in opposite directions. Whereas some studies suggest that people under-react to prior probabilities (base rate neglect), other studies find that people under-react to the likelihood of the data (conservatism). We argue
doi:10.1101/644534
fatcat:skrghmeiwrdorkrfotbhx4hvs4