I saw colleague Deborah Mayo casting, or rather trying to cast, aspersions on Bayesian philosophy by saying there is “no prior”. Bayesians might not agree, but it’s true. Mayo’s right. There is […]
Using P-Values To Diagnose “Trends” Is Invalid
Look at the picture, which is real data, but disguised to obscure its source. It is a physical measurement taken monthly by a recognized authority. The measurements are thought to have little […]
How To Do Predictive Statistics: Part X: Survival Analysis
Query: now that I’m a video master, would people like videos of these lessons? I don’t see how they’d help much, but who knows. Let me know below or via email. Next […]
How To Do Predictive Statistics: Part IX Stan — Logistic & Beta Regression
Review! We’re doing logistic and beta regression this time. These aren’t far apart, because the observable for both lives between 0 and 1; for logistic it is 0 or 1; for beta, […]
How To Do Predictive Statistics: Part VIII — Starting Stan
Review! You must at least review the first lessons—all class material is on one page for ease. I’ll have more words about the mysticism of simulation, but I’ve said it all before […]
The Doomsday Argument Is Doomed: Flawed Application Of Bayes
The WSJ on 27 June 2019 published an essay by William Poundstone on the hoary Doomsday Argument. Many are fooled by this equation, which contains a fundamental, even glaring, flaw. See the […]
How To Do Predictive Statistics: Part V New (Free) Software Multinomial Regression
Previous post in the series (or click above on Class). REVIEW! Download the code: mcmc.pred.R, mcmc.pred.examples.R. If you downloaded before, download again. This is version 0.22! Only the example code changed since […]
How To Do Predictive Statistics: Part I New (Free) Software Introduction
Introduction Here’s what we always want, but never get, using the old ways of doing statistics: The probability that some proposition Y is true given certain assumptions. Like this: (1) Pr(Y […]
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