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Several reviews of Deborah Mayo’s new book, Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars

Andrew Gelman · published 12 April 2019

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https://andrewgelman.com/2018/06/26/gonna-discussion-deborah-mayos-new-book/
andrewgelman.com
https://books.google.com/books?id=t6wKtAEACAAJ&printsec=frontcover
books.google.com
https://errorstatistics.com/2018/09/08/excursion-1-tour-i-beyond-probabilism-and-performance-severity-requirement/
errorstatistics.com
https://www.stat.columbia.edu/~gelman/research/published/gelman_hennig_full_discussion.pdf
stat.columbia.edu
https://errorstatistics.com/2019/03/05/blurbs-of-16-tours-statistical-inference-as-severe-testing-how-to-get-beyond-the-statistics-wars-sist/
errorstatistics.com
https://www.stat.columbia.edu/~gelman/research/unpublished/reversecausal_13oct05.pdf
stat.columbia.edu
https://www.stat.columbia.edu/~gelman/research/published/
stat.columbia.edu
https://arxiv.org/abs/1807.05996
arxiv.org
https://orgtheory.wordpress.com/2015/09/17/what-i-did-and-did-not-say-about-critical-thinking/
orgtheory.wordpress.com
https://xianblog.wordpress.com/2019/01/07/severe-testing-beyond-statistics-wars/
xianblog.wordpress.com
Elsewhere on statmodeling.stat.columbia.edu (6)
https://statmodeling.stat.columbia.edu/wp-content/uploads/2019/04/Excursion1_Tours-III.pdf
statmodeling.stat.columbia.edu
Philosophy and the practice of Bayesian statistics (with all the discussions!) Read at the source ↗
statmodeling.stat.columbia.edu
https://statmodeling.stat.columbia.edu/wp-content/uploads/2019/03/Severe-testing-Gelman-blog-2019.pdf
statmodeling.stat.columbia.edu
https://statmodeling.stat.columbia.edu/wp-content/uploads/2019/03/review.pdf
statmodeling.stat.columbia.edu
The puzzle: Why do scientists typically respond to legitimate scientific criticism in an angry, defensive, closed, non-scientific way? The answer: We’re trained to do this during the process of responding to peer review. Read at the source ↗
statmodeling.stat.columbia.edu
Confirmationist and falsificationist paradigms of science Read at the source ↗
statmodeling.stat.columbia.edu