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Null hypothesis statistical significance tests (NHST) are widely used inquantitative research in the empirical sciences including scientometrics.Nevertheless, since their introduction nearly a century ago significance testshave been controversial. Many researchers are not aware of the numerouscriticisms raised against NHST. As practiced, NHST has been characterized as anull ritual that is overused and too often misapplied and misinterpreted. NHSTis in fact a patchwork of two fundamentally different classical statisticaltesting models, often blended with some wishful quasi-Bayesian interpretations.This is undoubtedly a major reason why NHST is very often misunderstood. ButNHST also has intrinsic logical problems and the epistemic range of theinformation provided by such tests is much more limited than most researchersrecognize. In this article we introduce to the scientometric community thetheoretical origins of NHST, which is mostly absent from standard statisticaltextbooks, and we discuss some of the most prevalent problems relating to thepractice of NHST and trace these problems back to the mixup of the twodifferent theoretical origins. Finally, we illustrate some of themisunderstandings with examples from the scientometric literature and bringforward some modest recommendations for a more sound practice in quantitativedata analysis.

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