Growth of Experimental Knowledge Science.-eBay full of criticisms of Neyman-Pearson error statistics and had erected a store of counterintuitive. ing the growth of experimental knowledge. In contrast to the Error And The Growth Of Experimental Knowledge 2nd Edition. philosophical account of inductive inference and experimental knowledge. This paper is a response to Mayo's Error Statistics ES program, paying particular attention to.. error, hence provide for the growth of experimental knowledge.
The COVID-19 pandemic illustrates perfectly how the operation of science changes when questions of urgency, stakes, values and uncertainty collide -in the 'post-normal' regime. Well before the coronavirus pandemic, statisticians were debating how to prevent malpractice such as p-hacking, particularly when it could influence policy 1 . Now, computer modelling is in the limelight, with politicians presenting their policies as dictated by 'science' 2 . Yet there is no substantial aspect of this pandemic for which any researcher can currently provide precise, reliable numbers. Known unknowns include the prevalence and fatality and reproduction rates of the virus in Pandemic politics highlight how predictions need to be transparent and humble to invite insight, not blame.
In response to recommendations to redefine statistical significance to p ≤ .005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.
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