标题： 假设检验：两种不同理论的混淆，导致广泛的困惑和众多误解的基础 显示英文标题

标题： Null hypothesis significance tests: A mix-up of two different theories, the basis for widespread confusion and numerous misinterpretations

摘要： 显著性检验（NHST）广泛应用于包括科学计量学在内的实证科学的定量研究中。然而，自近一个世纪前引入以来，显著性检验一直颇具争议。许多研究人员并未意识到针对NHST提出的众多批评。在实际应用中，NHST 被描述为一种被过度使用且经常被误用和误解的“零假设仪式”。事实上，NHST 是两种本质上不同的经典统计检验模型的混合体，通常还掺杂一些准贝叶斯式的愿望解读。这无疑正是NHST经常被误解的主要原因之一。但NHST本身也存在内在逻辑问题，此类检验所提供的信息的认知范围远比大多数研究人员所认识到的更为有限。本文向科学计量学界介绍了NHST的理论起源（这在标准统计教材中大多缺失），并讨论了NHST实践中一些最普遍的问题，并追溯这些问题到两种不同理论起源的混淆。最后，我们通过科学计量文献中的例子来说明一些常见的误解，并提出一些关于定量数据分析更合理实践的谦逊建议。 显示英文摘要

摘要： Null hypothesis statistical significance tests (NHST) are widely used in quantitative research in the empirical sciences including scientometrics. Nevertheless, since their introduction nearly a century ago significance tests have been controversial. Many researchers are not aware of the numerous criticisms raised against NHST. As practiced, NHST has been characterized as a null ritual that is overused and too often misapplied and misinterpreted. NHST is in fact a patchwork of two fundamentally different classical statistical testing models, often blended with some wishful quasi-Bayesian interpretations. This is undoubtedly a major reason why NHST is very often misunderstood. But NHST also has intrinsic logical problems and the epistemic range of the information provided by such tests is much more limited than most researchers recognize. In this article we introduce to the scientometric community the theoretical origins of NHST, which is mostly absent from standard statistical textbooks, and we discuss some of the most prevalent problems relating to the practice of NHST and trace these problems back to the mixup of the two different theoretical origins. Finally, we illustrate some of the misunderstandings with examples from the scientometric literature and bring forward some modest recommendations for a more sound practice in quantitative data analysis.