Abstract

Human infants, apes and capuchin monkeys engage in intuitive statistics: they generate predictions from populations of objects to samples based on proportional information. This suggests that statistical reasoning might depend on some core knowledge that humans share with other primate species. To aid the reconstruction of the evolution of this capacity, we investigated whether intuitive statistical reasoning is also present in a species of Old World monkey. In a series of four experiments, 11 long-tailed macaques were offered different pairs of populations containing varying proportions of preferred versus neutral food items. One population always contained a higher proportion of preferred items than the other. An experimenter simultaneously drew one item out of each population, hid them in her fists and presented them to the monkeys to choose. Although some individuals performed well across most experiments, our results imply that long-tailed macaques as a group did not make statistical inferences from populations of food items to samples but rather relied on heuristics. These findings suggest that there may have been convergent evolution of this ability in New World monkeys and apes (including humans).

Highlights

  • The physical and social world can be described by statistical regularities: events co-occur with others repeatedly over time,& 2018 The Authors

  • Apes and capuchin monkeys engage in intuitive statistics: they generate predictions from populations of objects to samples based on proportional information

  • This suggests that statistical reasoning might depend on some core knowledge that humans share with other primate species

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Summary

Introduction

The physical and social world can be described by statistical regularities: events co-occur with others repeatedly over time,. At an implicit level, there is ample evidence that many aspects of statistical reasoning are already present in very young children: Preverbal infants (sometime as young as 6 months old) infer relationships between populations and samples [13], use statistical regularities to draw inferences about physical properties of objects [14] and proportions of objects to form expectations about new samples [15], as well as temporal and positional information of randomly moving objects to form expectations about which object is more likely to exit an urn [16,17]. An additional control experiment checked for the use of olfactory cues (Experiment 4)

Subjects
Experimental set-up
Study design and procedure
Coding procedure
Data analysis
Experiment 1a and b
Experiment 3
Experiment 4
General discussion
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