Learn about common pitfalls in statistics to look out for when reading scientific articles. Using a mix of lecture, discussion, and practice activities, participants will learn to identify misleading aspects of data visualizations, evidence of p-hacking, problems with pseudoreplication, and omissions in reporting of results. This resource is supported by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM013732 with the University of Utah’s Spencer S. Eccles Health Sciences Library. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. If you have any questions, please reach out to nto@nnlm.gov.
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