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Man as a Naïve Intuitive Statistician
| Peter Juslin |
| Department of Psychology, Uppsala University , Sweden |
In a seminal article from 1967, Peterson and Beach argued that probability theory and statistics provide a framework for understanding human inference and that psychological models based on these principles could account for human performance in a wide range of inferential tasks—that the mind could be likened to an intuitive statistician. Less than ten years later, Tversky and Kahneman (1974) the influential heuristics and biases program emphasized that people use simplifying intensional heuristics that cause characteristic deviations from statistics and probability theory, cognitive biases. The perspective of the naïve intuitive statistician (Fiedler & Juslin, 2006) integrates several aspects of these two research programs, claiming that people in general describe their sample experiences accurately (per the research on the intuitive statistician), but they are naïve with respect to more sophisticated sampling constraints and estimator properties of the samples encountered, sometimes contributing to persistent cognitive biases. The perspective of the naïve intuitive statistician is exemplified by applying it to explain overconfidence when people produce intuitive confidence intervals and why this format produces more overconfidence than other formally equivalent formats. The naïve sampling model (Juslin, Winman, & Hansson, 2006) implies that people accurately describe the sample information they have but are naïve in the sense that they uncritically take sample properties as estimates of population properties. A review demonstrates that the naïve sampling model accounts for the robust and important findings in previous research, as well as provides novel predictions that are confirmed, including a way to minimize the overconfidence with interval production.
Fiedler, K., & Juslin, P. (2006). Sampling as a key to understand adaptive cognition. New York : Cambridge University Press.
Peterson, C. R., & Beach, L. R. (1967). Man as an intuitive statistician. Psychological Bulletin, 68, 29-46.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131.
Juslin, P., Winman, A., & Hansson, P. (2006). The Naïve Intuitive Statistician: A Naïve Sampling Model of Intuitive Confidence Intervals . Manuscript, Department of Psychology, Uppsala University , Sweden .