Follow-up to the statement on p-values by ASA

The American Statistical Association Says [Mostly] No to p-values Norman Matloff has published a new post after receiving criticism and comments about stating “The ASA says No to p-values” in his post I wrote about some days ago. He defends his interpretation in this new post. However, I think, the interpretation of  the statement in a context different from the “Big data” field to which he is used to does not need to always be “Says No to p-values” but instead in many cases could be “Use p-values to assess the strength of the evidence and nothing else”.  However, “tests” with binary outcomes on …

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The American Statistical Association Says No to p-values

This post is copied from my Blog for Students and is to some extent off-topic but relevant to anybody doing research. Norman Matloff (2016) writes in his post: Sadly, the concept of p-values and significance testing forms the very core of statistics. A number of us have been pointing out for decades that p-values are at best underinformative and often misleading… Source: After 150 Years, the ASA Says No to p-values | Mad (Data) Scientist Yesterday, the statement by the American Statistics Association was published on-line in the journal “The American Statistician”. Many statisticians have been aware of the problems of …

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Rigor and Reproducibility

The NIH (USA, National Institutes of Health) has opened a new web site on the subject, which although focused on Biomedical research, provides a good account of current trends and problems, how to overcome them and guidelines that could be easily adapted for the rest of the Biosciences including UV-related research on plants. Rigor and Reproducibility  at NIH (USA) I propose that we follow the example of the Biophysical Society and write our own version of the guidelines adapted to the needs and problems of Plant UV-photobiology. Please give feedback on this idea by leaving a reply or comment.

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