Psychonomic Bulletin & Review

, Volume 22, Issue 1, pp 258–264 | Cite as

Whose statistical reasoning is facilitated by a causal structure intervention?

  • Simon McNairEmail author
  • Aidan Feeney
Brief Report


People often struggle when making Bayesian probabilistic estimates on the basis of competing sources of statistical evidence. Recently, Krynski and Tenenbaum (Journal of Experimental Psychology: General, 136, 430–450, 2007) proposed that a causal Bayesian framework accounts for peoples’ errors in Bayesian reasoning and showed that, by clarifying the causal relations among the pieces of evidence, judgments on a classic statistical reasoning problem could be significantly improved. We aimed to understand whose statistical reasoning is facilitated by the causal structure intervention. In Experiment 1, although we observed causal facilitation effects overall, the effect was confined to participants high in numeracy. We did not find an overall facilitation effect in Experiment 2 but did replicate the earlier interaction between numerical ability and the presence or absence of causal content. This effect held when we controlled for general cognitive ability and thinking disposition. Our results suggest that clarifying causal structure facilitates Bayesian judgments, but only for participants with sufficient understanding of basic concepts in probability and statistics.


Bayesian judgment Causal reasoning Base rate neglect Numeracy 


Author Notes

This research was funded by a Ph.D. studentship awarded to Simon McNair by the Department of Education and Learning, Northern Ireland.


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Copyright information

© Psychonomic Society, Inc. 2014

Authors and Affiliations

  1. 1.Centre for Decision Research, Leeds University Business SchoolUniversity of LeedsLeedsUK
  2. 2.Queen’s University BelfastBelfastUK

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