The so-called ‘replication [or reproducibility] crisis’ in science has, in part, been blamed on the use of significance tests, or p-values, to derive whether or not a scientific discovery is 'significant'.
RSS Conference programme lead, Daniel Farewell, introduced the keynote session which offered a variety of perspectives on significance tests from leading experts on the subject. Deborah Mayo, a statistical scientist and philosopher from the Department of Philosophy at Virginia Tech is author of the book, Statistical inference as Severe Testing. Fellow Virginia Tech professor, Aris Spanos, who has authored many papers on the subject including ‘Severe testing as a basic concept in a Neyman–Pearson philosophy of induction’ with Deborah Mayo back in 2006, brought his perspective from the field of econometrics. Richard Morey from the School of Psychology at Cardiff University, and who has just published a paper ‘Beyond statistics: accepting the null hypothesis in mature sciences’, talked from his background in Bayesian statistics and experimental psychology. Last, but certainly not least, David Cox brought his unique perspectives as one of the most influential thinkers in modern statistics.