The law of large numbers in children's diversity-based reasoning

Abstract

Abstract Adults increase the certainty of their inductive inferences by observing more diverse instances. However, most young children fail to do so. The present study tested the hypothesis that children's sensitivity to instance diversity is determined by three variables: ability to discriminate among instances (Discrimination); an intuition that large numbers of instances increase the strength of conclusion (Monotonicity); ability to detect subcategories and evaluate numerical differences between the subcategories, or Extraction. A total of 219 Chinese children aged 6 to 11 were tested for sensitivity to diversity by means of Discrimination, Monotonicity, and Extraction. The results indicated that children at all ages were able to discriminate instances and attend to set size. However, only 9- and 11-year-olds demonstrated Extraction and sensitivity to diversity. Furthermore, among all children diversity scores increased linearly with the level of Extraction. These results suggest that the law of large numbers plays a role in children's diversity-based reasoning. Keywords: ChildrenClassificationCognitive developmentDiversityInductive reasoningLarge numbersQuantitative reasoning Acknowledgments This work was supported by Key Discipline Fund of National 211 Project, China. (NSKD08014). Thanks to Sun Hongjin for his modification of language of the initial version of this manuscript. Thanks to Tang yan and Liu Diyuan for their help in collecting data. Notes 1Note that we did not compare basic- versus superordinate-level differences in monotonicity, because that ability is based simply on comparing the number of given arguments in each subcategory.