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The naïve intuitive statistician: A naïve sampling model of intuitive confidence intervals
Uppsala universitet.
Umeå University, Faculty of Social Sciences, Department of Psychology.
2007 (English)In: Psychological review, ISSN 0033-295X, E-ISSN 1939-1471, Vol. 114, no 3, 678-703 p.Article in journal (Refereed) Published
Abstract [en]

The perspective of the naïve intuitive statistician is outlined and applied to explain overconfidence when people produce intuitive confidence intervals and why this format leads to more overconfidence than other formally equivalent formats. Thenaïve sampling model 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. The authors discuss the naïve sampling model as a representative of models inspired by the naïve intuitive statistician.

Place, publisher, year, edition, pages
Washington: American Psychological Association , 2007. Vol. 114, no 3, 678-703 p.
Keyword [en]
subjective probability, calibration, confidence intervals, overconfidence, sampling model
URN: urn:nbn:se:umu:diva-2552DOI: 10.1037/0033-295X.114.3.678OAI: diva2:140738
Available from: 2007-09-17 Created: 2007-09-17 Last updated: 2011-06-20Bibliographically approved
In thesis
1. A naïve sampling model of intuitive confidence intervals
Open this publication in new window or tab >>A naïve sampling model of intuitive confidence intervals
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

A particular field in research on judgment and decision making (JDM) is concerned with realism of confidence in one’s knowledge. An interesting finding is the so-called format dependence effect, which implies that assessment of the same probability distribution generates different conclusions about over- or underconfidence depending on the assessment format. In particular, expressing a belief about some unknown continuous quantity (e.g., a stock value) in the form of an intuitive confidence interval is severely prone to overconfidence as compared to expressing the belief as an assessment of a probability judgment. This thesis gives a tentative account of this finding in terms of a Naïve Sampling Model, which assumes that people accurately describe their available information stored in memory, but they are naïve in the sense that they treat sample properties as proper estimators of population properties (Study 1). The effect of this naivety is directly investigated empirically in Study 2. A prediction that short-term memory is a constraining factor for sample size in judgment, suggesting that experience per se does not eliminate overconfidence is investigated and verified in Study 3. Age-related increments in overconfidence were observed with intuitive confidence interval but not for probability judgment (Study 4). This thesis suggests that no cognitive processing bias (e.g., Tversky & Kahneman, 1974) over and above naivety is needed to understand and explain the overconfidence “bias” with intuitive confidence interval and hence the format dependence effect.

Place, publisher, year, edition, pages
Umeå: Psykologi, 2007. 63 p.
overconfidence, subjective probability, sampling model, short-term memory, age-differences.
National Category
urn:nbn:se:umu:diva-1354 (URN)978-91-7264-368-0 (ISBN)
Public defence
2007-10-05, Bt102, Beteendevetarhuset, Umeå Universitet, Umeå, 10:00
Available from: 2007-09-17 Created: 2007-09-17 Last updated: 2013-12-19Bibliographically approved

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