The Optimal Standardization Factor for the Variance of the Normal Distribution: A Historical Perspective and Recommendations for Practice

Abstract Numerous variance estimators exist for the normal distribution, yet the unbiased estimator–commonly known as Bessel’s correction–remains the most widely used in practice. This article reviews various alternative estimators, that result from using different standardization factors for the sum of squares. It is demonstrated that there is no compelling reason to favor the unbiased variance estimator over other estimators and that better alternatives are available. Implications of these findings for applications involvings small sample size are discussed.

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Publication Details

Journal
Journal of Statistical Theory and Practice
Published
2026-03-23
DOI
https://doi.org/10.1007/s42519-026-00567-2
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

The Optimal Standardization Factor for the Variance of the Normal Distribution: A Historical Perspective and Recommendations for Practice

Dominic Edelmann
Journal of Statistical Theory and Practice
Statistical Distribution Estimation and Applications
article

The Optimal Standardization Factor for the Variance of the Normal Distribution: A Historical Perspective and Recommendations for Practice

Dominic Edelmann
article en

Abstract

Abstract Numerous variance estimators exist for the normal distribution, yet the unbiased estimator–commonly known as Bessel’s correction–remains the most widely used in practice. This article reviews various alternative estimators, that result from using different standardization factors for the sum of squares. It is demonstrated that there is no compelling reason to favor the unbiased variance estimator over other estimators and that better alternatives are available. Implications of these findings for applications involvings small sample size are discussed.

Journal of Statistical Theory and PracticeVol. 20(2)
German Cancer Research Center (DE), Heidelberg University (DE)
Openalex Percentile: Top 17%
Statistical Distribution Estimation and Applications
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