October 2007

Clay Public Lecture: "Technology-driven statistics"

The Clay Mathematics Institute and the Harvard Mathematics Department are sponsoring a lecture by Terry Speed from the Department of Statistics at Berkeley on "Technology-driven statistics," with a focus on the challenges presented to statistical theory and practice presented by the massive amounts of data that are generated by modern scientific instruments (microarrays, mass spectrometers, etc.). These issues have not yet been as salient in the social sciences, but they are clearly on the horizon. The talk is at 7PM tonight (Oct. 30) in Science Center B at Harvard.

Visualizing Electoral Data

Andy Eggers and I are currently working on a project on UK elections. We have collected a new dataset that covers detailed information on races for the House of Commons between 1950 and 1970; seven general elections overall. We have spent some time thinking about new ways to visualize electoral data and Andy has blogged about this here and here.

Income, partisanship, and voting

Andrew Gelman has an interesting post up about voting behavior in rich states and poor states, showing how voting patterns differ across the country when you condition on the income of the voters. There is not much of a relationship between per capita income and support for Democrats among poor voters, but there is a strong relationship among rich voters: rich voters in poor states are much more likely to support the Republicans than rich voters in rich states.

Visualizing UK Politicians

Since I saw Fernanda Viegas and Martin Wattenberg's presentation on Many Eyes a few weeks ago in our Applied Stats workshop, I've been itching to use their visualization tools on some of my own data. Tonight I made a treemap of the dataset of UK politicians that Jens Hainmueller and I have been developing.

Tim McCarver is a Bayesian with very strong priors....

The Red Sox beat the Indians last night in Game 5 of the ALCS, sending the series back to Fenway and enabling the majority of us at Harvard who are (at least fair-weather) Sox fans to, as Kevin Youkilis said last night, come down off the bridge for a few more days. Why do I bring this up? Well, after Boston's loss in Game 4, a commenter on this blog asked the following question:

How tall are you? No, really...

Continuing on the topic of self-reported health data, and how to correct for reporting (and other) biases, here an interesting paper on height and weight in the US. Those two measures have received a lot of interest in the past years, not least as components of the body-mass index BMI which is used to estimate the prevalence of obesity. BMI itself is not a great measure (more on that another day) but at least it’s relatively easy to collect via telephone and in-person interviews.