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

08:00 EDT 9th October 2019 | BioPortfolio

Summary of "Ten common statistical mistakes to watch out for when writing or reviewing a manuscript."

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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This article was published in the following journal.

Name: eLife
ISSN: 2050-084X
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Medical and Biotech [MESH] Definitions

Compositions written by hand, as one written before the invention or adoption of printing. A manuscript may also refer to a handwritten copy of an ancient author. A manuscript may be handwritten or typewritten as distinguished from a printed copy, especially the copy of a writer's work from which printed copies are made. (Webster, 3d ed)

The writing of history; the principles, theory, and history of historical writing; the product of historical writing. (Webster, 3d ed)

The practice of writing usually by a skilled or specialized writer focused on the reporting or dissemination of medical information for a target audience.

Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.

Application of statistical procedures to analyze specific observed or assumed facts from a particular study.

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