For years now, the utility of the P-value in scientific and statistical research has been under scrutiny – the debate shaped by concerns about the seeming over-reliance on p-values to decide what’s worth publishing or what’s worth pursuing. In 2016 the American Statistical Association released a statement on P-values, meant to remind readers that, “The P-values was never intended to be a substitute for scientific reasoning.” The statement also laid out six principles for how to approach P-values thoughtfully. The impact of that statement is the focus of this episode of Stats and Stories with guest Robert Matthews.

Robert Matthews is a visiting professor in the Department of Mathematics, Aston University in Birmingham, UK. Since the late 1990s, as a science writer, he has been reporting on the role of NHST in undermining the reliability of research for several publications including BBC Focus, and working as a consultant on both scientific and media issues for clients in the UK and abroad. His latest book, Chancing It: The Laws of Chance and How They Can Work for You is available now.

His research interests include the development of Bayesian methods to assess the credibility of new research findings – especially “out of the blue” claims; A 20-year study of why research findings fade over time and its connection to what’s now called “The Replication Crisis”; Investigations of the maths and science behind coincidences and “urban myths” like Murphy’s Law: “If something can go wrong, it will”; Applications of Decision Theory to cast light on the reliability (or otherwise) of earthquake predictions and weather forecasts; The first-ever derivation and experimental verification of a prediction from string theory.

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