Rethinking Hypothesis Tests

Rafael Izbicki,Luben M. C. Cabezas, Fernando A. B. Colugnatti, Rodrigo F. L. Lassance, Altay A. L. de Souza,Rafael B. Stern

arXiv (Cornell University)(2023)

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摘要
Null Hypothesis Significance Testing (NHST) have been a popular statistical tool across various scientific disciplines since the 1920s. However, the exclusive reliance on a p-value threshold of 0.05 has recently come under criticism; in particular, it is argued to have contributed significantly to the reproducibility crisis. We revisit some of the main issues associated with NHST and propose an alternative approach that is easy to implement and can address these concerns. Our proposed approach builds on equivalence tests and three-way decision procedures, which offer several advantages over the traditional NHST. We demonstrate the efficacy of our approach on real-world examples and show that it has many desirable properties.
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