Student SPHere 2008-09

The first day back is usually a good one. It's great to see people again and hear about all the travel over break. Many of my classmates went someplace warm over the holidays-- smart cookies! I'm scheming for a warm Spring Break, but we'll see if it actually plays out. Tom and I have some workaholic tendencies that usually prevent any travel during that time.

I had both of my classes on Tuesday. First up: Spatial with Sudipto Banerjee. I'm really looking forward to this class because I plan to expand and continue doing research in spatial statistics. We're using Sudipto's text (with Carlin and Gelfand), so I have at least skimmed the material before. It's a small class: seven registered, with only five attending yesterday.

We headed out a bit early to catch Obama's inauguration. It was pretty incredible seeing the university community gathering around televisions set up all over campus to watch the ceremonies. I was packed into a conference room in the dean's office with a few dozen other students, faculty, and staff, watching on a big screen. Every time they cut to a long shot of the millions of people on the mall, I couldn't help shaking my head in amazement. What a scene! I was impressed and heartened by Obama's speech-- it really does feel like a hopeful new beginning, despite the dire economic circumstances.

Then in the afternoon, I headed downstairs for Cavan Reilly's Bayes class. More familiar faces there, and a very familiar book-- Carlin and Louis! I know Cavan will be teaching at a higher level than the Bayes course for which I TA, but it certainly is a confidence boost to be using a text that I know so well. He started off with his version of the "Why do Bayes?" talk that every Bayesian eventually learns how to give. I think that I will face far less skepticism in my career than earlier generations of Bayesians, but there is still plenty of educating that can be done of frequentists and those who are outside the debate entirely. One great point he made was that in the sorting of statisticians into a 2x2 table with Bayesian/Frequentist on one axis and Parametric/Non-parametric on the other, it's the latter division that has a much greater impact on actual practice.