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Gallistel, C. R. – Psychological Review, 2009
Null hypotheses are simple, precise, and theoretically important. Conventional statistical analysis cannot support them; Bayesian analysis can. The challenge in a Bayesian analysis is to formulate a suitably vague alternative, because the vaguer the alternative is (the more it spreads out the unit mass of prior probability), the more the null is…
Descriptors: Bayesian Statistics, Statistical Analysis, Probability, Hypothesis Testing
Gershman, Samuel J.; Blei, David M.; Niv, Yael – Psychological Review, 2010
A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of "state classification" to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They…
Descriptors: Conditioning, Statistical Inference, Inferences, Bayesian Statistics
Miller, Ronald Mellado; Capaldi, E. John – Learning and Motivation, 2006
Sequential theory's memory model of learning has been successfully applied in response contingent instrumental conditioning experiments (Capaldi, 1966, 1967, 1994; Capaldi & Miller, 2003). However, it has not been systematically tested in nonresponse contingent Pavlovian conditioning experiments. The present experiments attempted to determine if…
Descriptors: Reinforcement, Training, Experiments, Probability
Hoffman, Aaron B.; Murphy, Gregory L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
Three experiments compared the learning of lower-dimensional family resemblance categories (4 dimensions) with the learning of higher-dimensional ones (8 dimensions). Category-learning models incorporating error-driven learning, hypothesis testing, or limited capacity attention predict that additional dimensions should either increase learning…
Descriptors: Experiments, Classical Conditioning, Probability, Comparative Analysis