再现性危机?-科学多样性与统计学中的p值问题

N. Minaka
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摘要

最近关于统计数据分析中p值的使用和滥用的争论揭示了科学研究的认识论多样性和科学的本质。自19世纪以来,包括卡尔·皮尔逊、罗纳德·费雪、杰西·内曼和埃根·皮尔逊在内的理论统计学家构建了现代统计学的数学基础,例如实验设计、抽样分布或假设检验等。然而,统计推理作为经验推理并不一定局限于内曼-皮尔逊的决策范式。任何一种非演绎推理——例如,诱拐——也使用统计学作为一种探索工具,在不同的假设和模型之间进行相对排名。我们不仅要了解统计方法和程序的正确使用,还要了解应用统计的每门科学的性质。
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Reproducibility Crisis?—Diversity of Science and the p -value Problem in Ststistics
The recent controversy over the use and abuse of p -values in statistical data analysis sheds a light on the epistemological diversity of scientific researches and the nature of science. Since the nineteenth century theoretical statisticians including Karl Pearson, Ronald A. Fisher, Jerzy Neyman, and Egon S.Pearson constructed the mathematical basis of modern statistics, for example, experimental design, sampling distributions, or hypothesis testing, etc. However, statistical reasoning as empirical inference is not necessarily limited to the Neyman-Pearson’s decision-making paradigm. Any kind of non-deductive inference—for example, abduction—also uses statistics as an exploratory tool for relative ranking among alternative hypotheses and models. We must understand not only the proper use of statistical methods and procedures but also the nature of each science to which statistics is applied.
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