Apparently I'm half-Bayesian

Steve Hsu links to a paper by Judea Pearl on Bayesian statistics and causality.

Judea Pearl: I turned Bayesian in 1971, as soon as I began reading Savage’s monograph The Foundations of Statistical Inference [Savage, 1962]. The arguments were unassailable: (i) It is plain silly to ignore what we know, (ii) It is natural and useful to cast what we know in the language of probabilities, and (iii) If our subjective probabilities are erroneous, their impact will get washed out in due time, as the number of observations increases.

Thirty years later, I am still a devout Bayesian in the sense of (i), but I now doubt the wisdom of (ii) and I know that, in general, (iii) is false. Like most Bayesians, I believe that the knowledge we carry in our skulls, be its origin experience, schooling or hearsay, is an invaluable resource in all human activity, and that combining this knowledge with empirical data is the key to scientific enquiry and intelligent behavior. Thus, in this broad sense, I am a still Bayesian. However, in order to be combined with data, our knowledge must first be cast in some formal language, and what I have come to realize in the past ten years is that the language of probability is not suitable for the task; the bulk of human knowledge is organized around causal, not probabilistic relationships, and the grammar of probability calculus is insufficient for capturing those relationships. Specifically, the building blocks of our scientific and everyday knowledge are elementary facts such as “mud does not cause rain” and “symptoms do not cause disease” and those facts, strangely enough, cannot be expressed in the vocabulary of probability calculus. It is for this reason that I consider myself only a half-Bayesian. ...

In that sense, I'm half-Bayesian as well. Coming at this from the direction of Thomist philosophy, I also do not regard probability as primary, but rather reality. One thing I might say differently is that the first things you know are mud and rain, and then you build a relationship between them with your mind [the third operation of the intellect].

John D. Cook

Today I found the website of a statistician who works with Bayesian clinical trials (among other things). My company is doing a Bayesian clinical trial on our newest product launch. He also works at M. D. Anderson Cancer Center, where a friend of mine is getting her PhD in Virology.

A selection of things that caught my eye:

Four reasons we don't apply the 80/20 rule [I think my whole life is the 80/20 rule, which probably really annoys some people. Do everything at the last minute? Check.]
Evaluate people at their best or worst? [I like this idea, but I think it applies mostly to people on the right hand of the bell curve. If your job is to work on an assembly line making stent-grafts, you damn well better have good average performance.]
All sorts of neat statistical software
What is a confidence interval? [Darn things keep being commonsensical no matter how hard statisticians try to make them obscure.]

h/t The Fourth Checkraise