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{{Publication
{{Publication
|title=Wasserstein RL, Lazar NA (2016) The ASA's statement on p-values: context, process, and purpose. The American Statistician [Epub ahead of print]. ย 
|title=Wasserstein RL, Lazar NA (2016) The ASA's statement on p-values: context, process, and purpose. The American Statistician 70:129-33.
|info=[http://dx.doi.org/10.1080/00031305.2016.1154108 Open Access]
|info=[http://dx.doi.org/10.1080/00031305.2016.1154108 Open Access]
|authors=Wasserstein RL, Lazar NA
|authors=Wasserstein RL, Lazar NA

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Wasserstein RL, Lazar NA (2016) The ASA's statement on p-values: context, process, and purpose. The American Statistician 70:129-33.

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Wasserstein RL, Lazar NA (2016) The American Statistician

Abstract: In February, 2014, George Cobb, Professor Emeritus of Mathematics and Statistics at Mount Holyoke College, posed these questions to an ASA discussion forum: Q: Why do so many colleges and grad schools teach p = .05? A: Because that's still what the scientific community and journal editors use. Q: Why do so many people still use p = 0.05? A: Because that's what they were taught in college or grad school. Cobbโ€™s concern was a long-worrisome circularity in the sociology of science based on the use of bright lines such as P < 0.05 : โ€œWe teach it because itโ€™s what we do; we do it because itโ€™s what we teach.โ€ This concern was brought to the attention of the ASA Board.

The ASA Board was also stimulated by highly visible discussions over the last few years. For example, ScienceNews (Siegfried, 2010) wrote: โ€œItโ€™s scienceโ€™s dirtiest secret: The โ€˜scientific methodโ€™ of testing hypotheses by statistical analysis stands on a flimsy foundation.โ€ A November, 2013, article in Phys.org Science News Wire (2013) cited โ€œnumerous deep flawsโ€ in null hypothesis significance testing. A ScienceNews article (Siegfried, 2014) on February 7, 2014, said โ€œstatistical techniques for testing hypothesesโ€ฆhave more flaws than Facebookโ€™s privacy policies.โ€ A week later, statistician and โ€œSimply Statisticsโ€ blogger Jeff Leek responded. โ€œThe problem is not that people use P-values poorly,โ€ Leek wrote, โ€œit is that the vast majority of data analysis is not performed by people properly trained to perform data analysisโ€ (Leek, 2014). ...


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