The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Intuitive statistics by 8-month-old infants
Open accessAbstract
Human learners make inductive inferences based on small amounts of data: we generalize from samples to populations and vice versa. The academic discipline of statistics formalizes these intuitive statistical inferences. What is the origin of this ability? We report six experiments investigating whether 8-month-old infants are “intuitive statisticians.” Our results showed that, given a sample, the infants were able to make inferences about the population from which the sample had been drawn. Conversely, given information about the entire population of relatively small size, the infants were able to make predictions about the sample. Our findings provide evidence that infants possess a powerful mechanism for inductive learning, either using heuristics or basic principles of probability. This ability to make inferences based on samples or information about the population develops early and in the absence of schooling or explicit teaching. Human infants may be rational learners from very early in development.
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Putting Education in “Educational” Apps: Lessons From the Science of Learning
Hirsh-Pasek, K., Zosh, J. M., Golinkoff, R. M., Gray, J. H., Robb, M. B., & Kaufman, J. (2015) · Psychological Science in the Public Interest · doi:10.1177/1529100615569721 · Cited by 1,049
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Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory.
Gopnik, A., & Wellman, H. M. (2012) · Psychological Bulletin · doi:10.1037/a0028044 · Cited by 663
Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars
Mayo, D. G. (2018) · doi:10.1017/9781107286184 · Cited by 376
The Naïve Utility Calculus: Computational Principles Underlying Commonsense Psychology
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Metadata
- Authors
- Xu, F., & Garcia, V.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2008-04
- Volume
- 105
- Issue
- 13
- Pages
- 5012-5015
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1999786027
- Cited by
- 356
- References
- 29
- FWCI
- 27.90
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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