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Testing the Bayesian confidence hypothesis

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If you have a question about this talk, please contact John Mollon.

The host for this talk is Professor Daniel Wolpert

Asking subjects to rate their confidence is one of the oldest procedures in psychophysics. Remarkably, quantitative models of confidence ratings have been scarce. The Bayesian confidence hypothesis states that an observer’s confidence rating is monotonically related to the posterior probability of their choice. Here, we test this hypothesis in three contexts: a) perceptual categorization (under both sensory noise and ambiguity); b) visual working memory (delayed estimation); c) visual judgment in science (interpreting scatterplots).

This talk is part of the Craik Club series.

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