Through a narrow window: Sample size and the perception of correlation.
Abstract
A theoretical analysis (Y. Kareev, 1995b) of the sampling distribution of correlations led to the surprising conclusion that the use of small samples has a potential advantage for the early detection of a correlation. This is so because the distribution is highly skewed, and the smaller the sample size, the more the distribution is skewed. This article describes 2 experiments that were designed as empirical tests of this conclusion. In Experiment 1 (N = 112), the authors compared the predictions of participants differing in their working-memory capacity (hence in the size of the samples they were likely to consider). In Experiment 2 (N = 144), the authors compared the predictions of participants who viewed samples of different sizes, whose size was determined by the authors. The results fully supported Y. Kareev's conclusion : In both experiments, participants with lower capacity (or smaller samples) indeed perceived the correlation as more extreme and were more accurate in their predictions.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Through a narrow window: Sample size and the perception of correlation. https://app.cochat.ai/papers/10.1037//0096-3445.126.3.278
- The paper
- Kareev, Y., Lieberman, I., & Lev, M. (1997). Through a narrow window: Sample size and the perception of correlation. Journal of Experimental Psychology: General. https://doi.org/10.1037//0096-3445.126.3.278
Data sources
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.