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- W1566416440 abstract "In the predecisional stage of information processing subjects often revise prior probabilities of several hypotheses on the basis of sample information. Multiple probability learning, defined as learning to associate events with their probabilities of occurrence, is often crucial for a consistent utilization of both prior and sampling distributions in probabilistic inference tasks. Two-choice probability learning studies have not provided much information about the manner in which subjects learn probabilities of events mainly because results of both perceptual learning and decision processes are confounded in the subject's prediction response. Extensions of the classical 2-choice paradigm to more than 2 alternatives and even to values of a continuous variable often suffer from the same weakness although sometimes response proportions and subjective probability estimates were collected simultaneously, indicating that they are fundamentally different dependent variables. The problem of measuring subjective probabilities is briefly discussed and some suggestions are made concerning research still to be done." @default.
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- W1566416440 title "Multiple probability learning" @default.
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- W1566416440 doi "https://doi.org/10.1016/0001-6918(70)90134-4" @default.
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