Null Hypothesis Significance Testing: a short tutorial
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Abstract
Although thoroughly criticized, null hypothesis significance testing is the statistical method of choice in biological, biomedical and social sciences to investigate if an effect is likely. In this short tutorial, I first summarize the concepts behind the method while pointing to common interpretation errors. I then present the related concepts of confidence intervals, effect size, and Bayesian factor, and discuss what should be reported in which context. The goal is to clarify concepts, present statistical issues that researchers face using the NHST framework and highlight good practices.
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2015. Null Hypothesis Significance Testing: a short tutorial. PeerJ PrePrints 3:e1050v1 https://doi.org/10.7287/peerj.preprints.1050v1Author comment
This article is my attempt to pack into a short paper all the major issues in interpreting and using NHST and also proposing a 'new' way to report statistical results.
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Competing Interests
The author declares they have no competing interests.
Author Contributions
Cyril R Pernet wrote the paper, reviewed drafts of the paper.
Funding
The author declares there was no funding for this work.
