Integrating Physical Constraints in Statistical Inference by 11-Month-Old Infants
Article first published online: 14 JUN 2010
Copyright © 2010 Cognitive Science Society, Inc.
Special Issue: 2009 Rumelhart Prize Special Issue Honoring Susan Carey
Volume 34, Issue 5, pages 885–908, July 2010
How to Cite
Denison, S. and Xu, F. (2010), Integrating Physical Constraints in Statistical Inference by 11-Month-Old Infants. Cognitive Science, 34: 885–908. doi: 10.1111/j.1551-6709.2010.01111.x
- Issue published online: 6 JUL 2010
- Article first published online: 14 JUN 2010
- Received 3 December 2009; received in revised form 14 April 2010; accepted 16 April 2010
- Statistical inference;
- Learning mechanisms in infancy;
- Physical reasoning;
- Probabilistic reasoning
Much research on cognitive development focuses either on early-emerging domain-specific knowledge or domain-general learning mechanisms. However, little research examines how these sources of knowledge interact. Previous research suggests that young infants can make inferences from samples to populations (Xu & Garcia, 2008) and 11- to 12.5-month-old infants can integrate psychological and physical knowledge in probabilistic reasoning (Teglas, Girotto, Gonzalez, & Bonatti, 2007; Xu & Denison, 2009). Here, we ask whether infants can integrate a physical constraint of immobility into a statistical inference mechanism. Results from three experiments suggest that, first, infants were able to use domain-specific knowledge to override statistical information, reasoning that sometimes a physical constraint is more informative than probabilistic information. Second, we provide the first evidence that infants are capable of applying domain-specific knowledge in probabilistic reasoning by using a physical constraint to exclude one set of objects while computing probabilities over the remaining sets.