Statistical Modeling, Causal Inference, and Social Science statmodeling.stat.columbia.edu

The stupidity, the criminal vandalism, the wanton destruction of information involved in dichotomisation

statmodeling.stat.columbia.edu·7h

What to do in 2026: Your statistics diary

statmodeling.stat.columbia.edu·10h

Our sanctimonious overlords (Kenneth Starr edition)

statmodeling.stat.columbia.edu·1d

What a multiverse good for anyway?

statmodeling.stat.columbia.edu·2d

The New York Young Republican Club, but this time with no butt plugs or dildos

statmodeling.stat.columbia.edu·2d

The fifth annual Cherry Blossom Prediction Competition is open!

statmodeling.stat.columbia.edu·3d

Sethi on “Betting on Geopolitical Violence”

statmodeling.stat.columbia.edu·3d

Survey Statistics: more on recalled vote

statmodeling.stat.columbia.edu·4d

Some Open Problems in Probability that are Relevant to Applied Statistics (my talk this Wed noon at the Columbia statistics department student seminar)

statmodeling.stat.columbia.edu·4d

A consensus–but it’s a consensus of uncertainty.

statmodeling.stat.columbia.edu·5d

Everything I ever needed to know in life I learned from the men in the Epstein files

statmodeling.stat.columbia.edu·5d

Review of string theory book from 2004 brings up interesting questions regarding age-period-cohort effects in the sociology of science

statmodeling.stat.columbia.edu·6d

Hey, here’s $100,000 down the drain!

statmodeling.stat.columbia.edu·1w

The anti-Bayesian is standing at the back window with a shotgun, scanning for priors coming over the hill, while a million assumptions just walk right into his house through the front door. (also, an interesting point by Yann LeCun about human language)

statmodeling.stat.columbia.edu·1w

Sunstein on Kissinger: No opinion on the whole war criminal thing, but the generosity that he showed when talking about Star Wars [the movie, not the weapons program] was “incomparable”

statmodeling.stat.columbia.edu·1w

Softly, effectively, in the age of genAI

statmodeling.stat.columbia.edu·1w

“Statistics is widely understood to provide a body of techniques for ‘modeling data.’”

statmodeling.stat.columbia.edu·1w

Survey Statistics: 5 flavors of calibration

statmodeling.stat.columbia.edu·1w

“Parallelizing MCMC Across the Sequence Length”: This one is really cool.

statmodeling.stat.columbia.edu·1w

Postdoc in Milan on scalability for high-dimensional Bayesian learning

statmodeling.stat.columbia.edu·1w

Loading...Loading more...