This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and shar

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• Philosophy of science
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• Inductive reasoning
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• Inference
• Psychology
• Causal model
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Preschoolers sample from probability distributions Stephanie Denison () Elizabeth Baraff Bonawitz (liz ) Alison Gopnik () Thomas L. Griffiths (tom griffiths@berkeley.

Source URL: ccdlab.rutgers.edu

• Statistics
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UMRIDA: Bringing Uncertainty Management and Robust Design Methodologies to Industrial Levels Charles Hirsch, Dirk Wunsch, Thomas Deconinck Numeca International

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Editorial The new issue of the ISLP Newsletter is here! In this issue we describe ISLP project news in brief and bring you many other

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• Mathematics education
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(Brief) Introduction to (Selected Aspects of) Natural Language Processing and Machine Learning Jaromir Savelka and Matthias Grabmair Intelligent Systems Program University of Pittsburgh

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• Computational linguistics
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Rational Randomness: The role of sampling in an algorithmic account of preschooler’s causal learning Bonawitz, E., Gopnik, A., Denison, S., Griffiths, T. L. University of California, Berkeley; Berkeley, CA 94720

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Children and adults differ in their strategies for social learning Falk Lieder1 () Zi Lin Sim1 () Jane C. Hu ()

Source URL: cocosci.berkeley.edu

• Cognitive science
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Forum Probabilistic models, learning algorithms, and response variability: sampling in cognitive development Elizabeth Bonawitz1, Stephanie Denison2, Thomas L. Griffiths3, and Alison Gopnik3

Source URL: cocosci.berkeley.edu

• Statistical inference
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References should follow the Chicago Humanities style

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Introduction to the R Project for Statistical Computing for use at ITC D G Rossiter University of Twente Faculty of Geo-information Science & Earth Observation (ITC)

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