Authors
Aidan Lyon
University of Maryland, College Park
Abstract
It is usually supposed that the central limit theorem explains why various quantities we find in nature are approximately normally distributed—people's heights, examination grades, snowflake sizes, and so on. This sort of explanation is found in many textbooks across the sciences, particularly in biology, economics, and sociology. Contrary to this received wisdom, I argue that in many cases we are not justified in claiming that the central limit theorem explains why a particular quantity is normally distributed, and that in some cases, we are actually wrong. 1 Introduction2 Normal Distributions and the Central Limit Theorem2.1 Normal distributions2.2 The central limit theorem2.3 Terminology3 Explaining Normality3.1 Loaves of bread3.2 Varying variances and probability densities3.3 Tensile strengths and problems with summation3.4 Products of factors and log-normal distributions3.5 Transforming factors and sub-factors3.6 Transformations of quantities3.7 Quantitative genetics3.8 Inference to the best explanation4 Maximum Entropy Explanations5 Conclusion
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DOI 10.1093/bjps/axs046
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References found in this work BETA

Laws and Symmetry.Bas C. van Fraassen - 1989 - Oxford, England: Oxford University Press.
Laws and Symmetry.Bas C. van Fraassen - 1989 - Revue Philosophique de la France Et de l'Etranger 182 (3):327-329.
Fact, Fiction, and Forecast.Nelson Goodman - 1955 - Philosophy 31 (118):268-269.

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Citations of this work BETA

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Galton, Reversion and the Quincunx: The Rise of Statistical Explanation.André Ariew, Yasha Rohwer & Collin Rice - 2017 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 66:63-72.
In Defence of Explanatory Realism.Stefan Roski - 2021 - Synthese 199 (5-6):14121-14141.

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