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Article summary:
1. This article provides a list of ten common statistical mistakes that are often found in scientific literature.
2. It offers advice on how authors, reviewers and readers can identify and resolve these mistakes to avoid them in the future.
3. The article also encourages readers to offer alternative solutions by annotating the online version of the article.
Article analysis:
The article is written in a clear and concise manner, making it easy to understand for readers from any scientific background. The authors provide detailed explanations of each mistake, as well as advice on how to detect and solve them. Furthermore, they encourage readers to offer alternative solutions by annotating the online version of the article, which allows for a diversity of ideas and perspectives.
The article does not appear to be biased or one-sided; it presents both sides equally and does not make unsupported claims or omit counterarguments. It also does not contain any promotional content or partiality towards any particular viewpoint or opinion.
The only potential issue with this article is that it does not discuss possible risks associated with some of the mistakes mentioned, such as inflated effect sizes due to inadequate control groups or conditions. This could lead readers to underestimate the potential consequences of these mistakes if they are not addressed properly.