I will use this banner for posts that seem relevant for our Synthese Topical Collection on Severity and learning from error (CFP here). Many of the issues in today’s meta-methodology interconnect with philosophy of statistics and epistemology, and I am keen to highlight posts that touch on this. Consider preregistration. It’s a welcome consequence of today’s [ ]
I am pleased to share that Professor Peter McCullagh has received the 2026 Sir David R. Cox Foundations of Statistics Award, given by the American Statistical Association (ASA). Below is the announcement from the JUNE 1, 2026 issue of AMSTAT NEWS. Peter McCullagh to Give David Cox Foundations of Statistics Lecture For foundational contributions to [ ]
Can You Make Me More Capable? Of Art, Astrophysics and AI Since the pandemic, I have returned to an old passion of mine–drawing, especially life drawing. I have always loved it. One year I even won my high school s art award. Over the years, academic work had crowded it out, except for the occasional conference [ ]
Last week, July 15, was Sir David Cox’s birthday. [1] It was 23 years ago that I first got to know Cox after I (boldly) invited him to be in a session I was organizing on philosophy of statistics for the Second Erich L. Lehmann Symposium held in May 19–22, 2004; Rice University, Texas. I [ ]
I hope that many readers of this blog will consider contributing to this! ANNOUNCEMENT SEV26 Synthese Topical Collection CFP: Severity and Learning from Error This Topical Collection examines how inquiry learns from error by focusing on a basic principle of evidence in science, statistics, medicine, law, epistemology, and day-to-day learning: a claim is not well-tested, known [ ]
In my opinion, a great deal of confusion about statistics can be traced to the fact that the point estimate is seen as being the be all and end all, the expression of uncertainty being forgotten .to provide a point estimate without also providing a standard error is, indeed, an all too standard error. Stephen Senn: [ ]
In giving some informal remarks about power at a seminar a couple of weeks ago, I proposed that the tendency to turn the notion of power on its head might be avoided by imagining we need to define a test s error probabilities in terms of its power alone. We can refer to the power against [ ]
30 years ago today, Chicago Press sent me a draft version of this cover for Error and the Growth of Experimental Knowledge for my approval (except the fuchsia and mustard in ERROR were switched). At first I thought it was so cartoony that it might be an April 1 joke! I had sent them a [ ]
Given how much I’ve blogged about the 2016 ASA p-value statement, the 2019 Executive Editor s editorial in The American Statistician (TAS), the 2020 ASA (President’s) Task Force, and the various casualties of the related teeth pulling, I thought I should say something about the recent article by Robert Matthews in Significance (March 2026): “The ASA [ ]
The concept of a test s power, originating in Neyman-Pearson s early work, by and large, is a pre-data concept for purposes of specifying a test (notably, determining worthwhile sample size), and choosing between tests. In some papers, however, Neyman lists a third goal for power: to interpret test results post data much in the spirit of [ ]
The mayor of NYC offered $30 an hour to help shovel the ~ 30 inches of snow that fell last Sunday and Monday. From what I hear, it was a very effective program. Here s a little power puzzle to very easily shovel through [1] Suppose you are reading about a result x that is just [ ]
I often say that the most misunderstood concept in error statistics is power. One week ago, stuck in the blizzard of 2026 in NYC —exciting, if also a bit unnerving, with airports closed for two and a half days and no certainty of when I might fly out—I began collecting the many power howlers I ve [ ]
The following is the February stop of our leisurely cruise (meeting 6 from my 2020 Seminar at the LSE). There was a guest speaker, Professor David Hand. Slides and videos are below. Ship StatInfasSt may head back to port or continue for an additional stop or two, if there is interest. Although I often say [ ]
From time to time I hear of an application of the severe testing philosophy in intriguing ways in fields I know very little about. An example is a recent article by cognitive psychologist Jeffrey Bowers and colleagues (2023): “On the importance of severely testing deep learning models of cognition” (abstract below). Because deep neural networks [ ]
Our second stop in 2026 on the leisurely tour of SIST is Excursion 4 Tour II which you can read here. This criticism of statistical significance tests takes a number of forms. Here I consider the best known. The bottom line is that one should not suppose that quantities measuring different things ought to be [ ]