David Blackwell was already retired by the time I came to Berkeley, and probably our closest connection was that I taught the class in decision theory that he used to teach. I enjoyed that class a lot, partly because it took me out of my usual comfort zone of statistical inference and data analysis toward something more theoretical and mathematical. Blackwell was one of the legendary figures in the department at that time and was also one of the most tolerant of alternative approaches to statistics, perhaps because of combination of a mathematical background, applied research in the war and after (which I learned about in this recent obituary), and personal experiences,

Blackwell may be best known in statistics for the Rao-Blackwell theorem. Rao, of course, is also famoust for the Cramer-Rao lower bound. Both theorems relate to minimum-variance statistical estimators.

Here’s a quote from Thomas (Jesus’s dad) Ferguson in Blackwell’s obituary:

He went from one area to another, and he’d write a fundamental paper in each, He would come into a field that had been well studied and find something really new that was remarkable. That was his forte.

And here’s a quote from Peter Bickel, who in 1967 published an important paper on Bayesian inference:

He had this great talent for making things appear simple, He liked elegance and simplicity. That is the ultimate best thing in mathematics, if you have an insight that something seemingly complicated is really simple, but simple after the fact.

And here’s Blackwell himself, from 1983:

Basically, I’m not interested in doing research and I never have been, I’m interested in understanding, which is quite a different thing. And often to understand something you have to work it out yourself because no one else has done it.

I’m surprised to hear Blackwell consider “research” and “understanding” to be different, as to me they seem to be closely related. One of the most interesting areas of statistical research today is on methods for understanding models as maps from data to predictions. As Blackwell and his collaborators demonstrated, even the understanding of simple statistical inferences is not a simple task.

P.S. According to the obituary, Blackwell was denied jobs at Princeton and the University of California because of racial discrimination, and so, a year after receiving his Ph.D., he “sent out applications to 104 black colleges on the assumption that no other schools would hire him.” The bit about the 104 job applications surprised me. Nowadays I know that people send out hundreds of job applications, but I didn’t know that this was done back in 1943. I somehow thought the academic world was more self-contained back then.

P.P.S. My Barnard College colleague Rajiv Sethi discusses Blackwell’s research as seen by economists.

The Illinois Alumni Association magazine did an interesting article on David Blackwell, available here.

http://www.stat.berkeley.edu/images/stories/docs/…

He gave one of the two best talks I ever heard. No slides, no Powerpoint, just half a page of paper and a piece of chalk. (The other one of the two was given by Kakutani with exactly the same equipment. I can't believe it's his daughter who writes such aggressive book reviews in the NYT)

Blackwell may have thought what he was doing was 'simply explaining' or 'understanding' but his papers are tough – very good stuff – but tough. I heard him give a talk at Carolina (which was great) and always wondered what it would be like to be able to think like that. (I also thought that when I heard a presentation by Feynman which was extremely funny and unbelievably abstract.)

Dr. Gelman, you comment "One of the most interesting areas of statistical research today is on methods for understanding models as maps from data to predictions" – can you give some references? – thanks.

Charlie: Unfortunately I don't have any great references on this. My impression is that the problems involved in understanding models have been difficult to formulate and have not been studied as much as they should.

http://www.visionaryproject.org/blackwelldavid/ videos of Blackwell are stunning.