Ten common statistical mistakes to watch out for when writing or reviewing a manuscript

Originally broadcast 15-Sep-23.
Discover the most common statistical and reporting errors in the scientific literature and learn reliable methods to increase the rigor of your data and its reporting.
In this webinar, you will:
Discover the benefits of transparent reporting;
Explore common statistical mistakes and the solutions to them;
Gain the tools to assess the reliability of your findings and of those reported in the literature.
Some scientific papers are unbelievable as they showcase experimental tour de force that we did not think possible. These papers astound us with their groundbreaking findings and meticulous methodologies.
However, alongside these unbelievably good papers, there are papers that are unbelievable due to the pervasive presence of statistical mistakes that undermine their credibility. Whether due to negligence, lack of expertise, or a rush to publish, these errors cast doubt on the validity of the reported results and conclusions.
In this talk, JJ Orban de Xivry will delve into the ten most common statistical mistakes that plague scientific research (Makin and Orban de Xivry, eLife, 2019).
With a focus on identifying these errors, he will shed light on the detrimental impact they have on the reliability of scientific findings. By identifying and rectifying statistical mistakes, researchers can ensure the foundation of their field of study.
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