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Johnston, Angie M.; Johnson, Samuel G. B.; Koven, Marissa L.; Keil, Frank C. – Developmental Science, 2017
Like scientists, children seek ways to explain causal systems in the world. But are children scientists in the strict Bayesian tradition of maximizing posterior probability? Or do they attend to other explanatory considerations, as laypeople and scientists--such as Einstein--do? Four experiments support the latter possibility. In particular, we…
Descriptors: Young Children, Thinking Skills, Inferences, Bayesian Statistics
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Yurovsky, Daniel; Boyer, Ty W.; Smith, Linda B.; Yu, Chen – Developmental Science, 2013
Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the "dilution effect,"…
Descriptors: Cues, Prediction, Infants, Cognitive Ability
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Denison, Stephanie; Xu, Fei – Developmental Science, 2010
Previous research has revealed that infants can reason correctly about single-event probabilities with small but not large set sizes (Bonatti, 2008; Teglas "et al.", 2007). The current study asks whether infants can make predictions regarding single-event probability with large set sizes using a novel procedure. Infants completed two trials: A…
Descriptors: Prediction, Infants, Probability, Preschool Children