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Famous people with Tourette’s syndrome

I was curious so I went over to this wikipedia page, which at the time of this writing includes: musicians/composers 12 actors/performers/motivational speakers 10 athletes 6 writers/journalists 4 politicians/activists 3 scientists 3 rich people / political commentators 2 Some of the people fell into multiple categories; for them, I picked one....

Is an improper uniform prior informative? It isn’t by any accepted measure of information I know of

Yesterday I was among those copied when a correspondent wrote something I’d seen before and which had always stood out as totally wrong to me in the statistical context I usually work within (mainly regression coefficients for generalized linear models with canonical link functions like the normal-linear, binomial-logistic, and log-linear proportional-hazards...

“Measuring the sensitivity of Gaussian processes to kernel choice”

Rob Trangucci points us to this paper by William Stephenson, Soumya Ghosh, Tin Nguyen, Mikhail Yurochkin, Sameer Deshpande, and Tamara Broderick. I’m posting it here because it involves GPs, so Aki should be interested too. Related ideas: Static sensitivity analysis (for example section 6.3 here) An automatic finite-sample robustness metric (by...

“Sponsored products related to this item”

I happened to look up the classic programming book Code Complete (fully, “Code Complete: A Practical Handbook of Software Construction, Second Edition,” by Steve McConnell) and I learned two amusing things when scrolling down the page: 1. It says, “You last purchased this item on September 9, 2004.” Wow! I bought it, probably on Bob Carpenter’s...

A counterexample to the potential-outcomes model for causal inference

Something came up where I realized I was wrong. It wasn’t a mathematical error; it was a statistical model that was misleading when I tried to align it with reality. And this made me realize that there was something I was misunderstanding about potential outcomes and casual inference. And then I thought: If I’m confused, maybe some of you will be...

Some open questions in chess

– When played optimally, is pawn race a win for white, black, or a draw? – Could I beat a grandmaster if he was down a queen? I tried playing Stockfish with it down a Q and a R, and I won easily. (Yeah!) I suspect I could beat it just starting up a queen. But Stockfish plays assuming I’ll play optimally. Essentially it’s just trying to lose gracefully....

Not-so-recently in the sister blog

The role of covariation versus mechanism information in causal attribution: Traditional approaches to causal attribution propose that information about covariation of factors is used to identify causes of events. In contrast, we present a series of studies showing that people seek out and prefer information about causal mechanisms rather than information...

The Feud

I just read the above-titled book by Alex Beam and I really enjoyed it. I’ve been a fan of Beam for a long time; he just has this wonderful equanimous style. The thing that amazes me is that the book got published at all. It’s subtitle is “Vladimir Nabokov, Edmund Wilson, and the End of a Beautiful Friendship.” Sounds like it would sell about 4...

How to interpret inferential statistics when your data aren’t a random sample

Someone named Adam writes: I’m having a bit of a ‘crisis’ of confidence regarding inferential statistics. I’ve been reading some of the work by Stephen Gorard (e.g. “Against Inferential Statistics”) and David Freedman and Richard Berk (e.g. “Statistical Assumptions as empirical commitments”). These authors appear to be saying this: (1) Inferential...

A regression puzzle . . . and its solution

Alex Tabarrok writes: Here’s a regression puzzle courtesy of Advanced NFL Stats from a few years ago and pointed to recently by Holden Karnofsky from his interesting new blog, ColdTakes. The nominal issue is how to figure our whether Aaron Rodgers is underpaid or overpaid given data on salaries and expected points added per game. Assume that these...

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