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Denison, Stephanie; Bonawitz, Elizabeth; Gopnik, Alison; Griffiths, Thomas L. – Cognition, 2013
We present a proposal--"The Sampling Hypothesis"--suggesting that the variability in young children's responses may be part of a rational strategy for inductive inference. In particular, we argue that young learners may be randomly sampling from the set of possible hypotheses that explain the observed data, producing different hypotheses with…
Descriptors: Sampling, Probability, Preschool Children, Inferences
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Douven, Igor; Verbrugge, Sara – Cognition, 2010
According to Adams's Thesis, the acceptability of an indicative conditional sentence goes by the conditional probability of its consequent given its antecedent. We test, for the first time, whether this thesis is descriptively correct and show that it is not; in particular, we show that it yields the wrong predictions for people's judgments of the…
Descriptors: Prediction, Probability, Inferences, Sentences
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Perfors, Amy; Tenenbaum, Joshua B.; Griffiths, Thomas L.; Xu, Fei – Cognition, 2011
We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive development. Our goal is to provide an intuitive and accessible guide to the "what", the "how", and the "why" of the Bayesian approach: what sorts of problems and data the framework is most relevant for, and how and why it may be useful for…
Descriptors: Bayesian Statistics, Cognitive Psychology, Inferences, Cognitive Development
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Fisher, Anna V.; Matlen, Bryan J.; Godwin, Karrie E. – Cognition, 2011
Prior research suggests that preschoolers can generalize object properties based on category information conveyed by semantically-similar labels. However, previous research did not control for co-occurrence probability of labels in natural speech. The current studies re-assessed children's generalization with semantically-similar labels.…
Descriptors: Semantics, Generalization, Probability, Inferences
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Hertwig, Ralph; Benz, Bjorn; Krauss, Stefan – Cognition, 2008
According to the conjunction rule, the probability of A "and" B cannot exceed the probability of either single event. This rule reads "and" in terms of the logical operator [inverted v], interpreting A and B as an intersection of two events. As linguists have long argued, in natural language "and" can convey a wide range of relationships between…
Descriptors: Semantics, Form Classes (Languages), Probability, Inferences