The significance test is perhaps the most used statistical procedure in the world, though has never been without its detractors. This is the second of two posts exploring Neyman's frequentist arguments against the significance test; if you have not read Part 1, you should do so before continuing (“The frequentist case against the significance test, part 1”).Neyman offered two major arguments against the significance test:The significance test fails as an…
This winter, in my ACT8595 course, I asked my students (that was some homework) to prove that it was possible to derive the conditional distribution when we have a Student-t random vector (and to get the analytical expression of the later). But before, let us recall a standard result about the Gaussian vector. If is a Gaussian random vector, i.e. then has a Gaussian distribution. More precisely, it is a distribution, with and is the Schur…
This Monday, in the ACT8595 course, we came back on elliptical distributions and conditional independence (here is an old post on de Finetti’s theorem, and the extension to Hewitt-Savage’s). I have shown simulations, to illustrate those two...
In my first post, I described the general logic of Bayes factors. I will continue discussing the general logic of Bayes factor, while introducing some of the basic functionality of the BayesFactor package.Recap: What is a Bayes factor?The Bayes factor is the relative evidence provided by the data for comparing two statistical models. It has two equivalent definitions:The Bayes factor is the relative predictive success between two hypotheses: it is…
I love Saint Patrick’s Day for, at least, two reasons. The first one is that, on March 17th, you can play out loud The Pogues, the second one is that it’s the only day in the year when I really enjoy getting a Guiness in a pub. And Guiness is important in statistical science (I did mention a couple of hours ago – on this blog – that beers were…
