Null hypothesis significance testing: a short tutorial

Cyril Pernet

doi:10.12688/f1000research.6963.3

Null hypothesis significance testing: a short tutorial

Research output: Contribution to journal › Article › peer-review

Abstract

Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of significance (Fisher) and test of acceptance (Newman-Pearson) and point to common interpretation errors regarding the p-value. I then present the related concepts of confidence intervals and again point to common interpretation errors. Finally, I discuss what should be reported in which context. The goal is to clarify concepts to avoid interpretation errors and propose reporting practices.

Original language	English
Pages (from-to)	621
Number of pages	6
Journal	F1000Research
Volume	4
DOIs	https://doi.org/10.12688/f1000research.6963.3
Publication status	Published - 12 Oct 2017

Keywords

null hypothesis significance testing
review

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10.12688/f1000research.6963.3Licence: Creative Commons: Attribution (CC-BY)

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Copyright: © 2016 Pernet C. This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Other version, 1.41 MBLicence: Creative Commons: Attribution (CC-BY)

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Null hypothesis significance testing: a short tutorial

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