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.New episodes of Stats+Stories is returning in two weeks.