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Ten common statistical mistakes to watch out for when writing or reviewing a manuscript
Tamar R Makin1, Jean-Jacques Orban de Xivry2,3
1Institute of Cognitive Neuroscience, University College London, London, United Kingdom.
Abstract:
Inspired by broader efforts to make the conclusions of scientific research more robust, we have compiled a list of some of the most common statistical mistakes that appear in the scientific literature. The mistakes have their origins in ineffective experimental designs, inappropriate analyses and/or flawed reasoning. We provide advice on how authors, reviewers and readers can identify and resolve these mistakes and, we hope, avoid them in the future.
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