Statistical Modeling (Andrew Gelman) statmodeling.stat.columbia.edu

Most Popular Posts of 2024

statmodeling.stat.columbia.edu·71w·Hacker News

A very interesting discussion by Roy Sorenson of the interesting-number paradox

statmodeling.stat.columbia.edu·71w

Sorry, NYT, but, yes, “Equidistant Letter Sequences in the Book of Genesis” was junk science

statmodeling.stat.columbia.edu·71w

Bayesian inference (and mathematical reasoning more generally) isn’t just about getting the answer; it’s also about clarifying the mapping from assumptions to i...

statmodeling.stat.columbia.edu·71w

Announcing two new members of our blogging team . . .

statmodeling.stat.columbia.edu·71w

Softmax is on the log, not the logit scale

statmodeling.stat.columbia.edu·72w·Hacker News

Data manipulation in the world of long-distance swimming!

statmodeling.stat.columbia.edu·72w

How to cheat at Codenames; cheating at board games more generally

statmodeling.stat.columbia.edu·72w

Addressing legitimate counterarguments in a scientific review: The challenge of being an insider

statmodeling.stat.columbia.edu·72w

The marginalization or Jeffreys-Lindley paradox: it’s already been resolved.

statmodeling.stat.columbia.edu·72w

Stanford medical school professor misrepresents what I wrote (but I kind of understand where he’s coming from)

statmodeling.stat.columbia.edu·72w

The true meaning of the alzabo

statmodeling.stat.columbia.edu·72w

Delicate language for talking about statistical guarantees

statmodeling.stat.columbia.edu·72w

“Accounting for Nonresponse in Election Polls: Total Margin of Error”

statmodeling.stat.columbia.edu·72w

How did the press do on that “black spatula” story? Not so great.

statmodeling.stat.columbia.edu·73w

He took public funds and falsified his data. Are they gonna make him pay back the $19 million?

statmodeling.stat.columbia.edu·73w

Applications of (Bayesian) variational inference?

statmodeling.stat.columbia.edu·73w

Iterative imputation and incoherent Gibbs sampling

statmodeling.stat.columbia.edu·73w

“The Exceptions: Nancy Hopkins, MIT, and the Fight for Women in Science”

statmodeling.stat.columbia.edu·73w

The well-meaning but useless or counterproductive social science establishment

statmodeling.stat.columbia.edu·73w

Log in to enable infinite scrolling