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统计学的基本概念:阐释与例证

Fundamental concepts in statistics: elucidation and illustration.

作者信息

Curran-Everett D, Taylor S, Kafadar K

机构信息

Departments of Pediatrics and of Preventive Medicine and Biometrics, School of Medicine, University of Colorado Health Sciences Center, Denver, 80217-3364, USA.

出版信息

J Appl Physiol (1985). 1998 Sep;85(3):775-86. doi: 10.1152/jappl.1998.85.3.775.

Abstract

Fundamental concepts in statistics form the cornerstone of scientific inquiry. If we fail to understand fully these fundamental concepts, then the scientific conclusions we reach are more likely to be wrong. This is more than supposition: for 60 years, statisticians have warned that the scientific literature harbors misunderstandings about basic statistical concepts. Original articles published in 1996 by the American Physiological Society's journals fared no better in their handling of basic statistical concepts. In this review, we summarize the two main scientific uses of statistics: hypothesis testing and estimation. Most scientists use statistics solely for hypothesis testing; often, however, estimation is more useful. We also illustrate the concepts of variability and uncertainty, and we demonstrate the essential distinction between statistical significance and scientific importance. An understanding of concepts such as variability, uncertainty, and significance is necessary, but it is not sufficient; we show also that the numerical results of statistical analyses have limitations.

摘要

统计学的基本概念构成了科学探究的基石。如果我们不能充分理解这些基本概念,那么我们得出的科学结论就更有可能是错误的。这并非只是猜测:60年来,统计学家一直警告说,科学文献中存在对基本统计概念的误解。美国生理学会期刊在1996年发表的原创文章在处理基本统计概念方面也没有更好的表现。在这篇综述中,我们总结了统计学的两个主要科学用途:假设检验和估计。大多数科学家仅将统计学用于假设检验;然而,通常情况下,估计更为有用。我们还阐述了变异性和不确定性的概念,并论证了统计显著性与科学重要性之间的本质区别。理解变异性、不确定性和显著性等概念是必要的,但还不够;我们还表明,统计分析的数值结果存在局限性。

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