Category: Statistics

Tom Wolfe

I’m a big Tom Wolfe fan. My favorites are The Painted Word and From Bauhaus to Our House, and I have no patience for the boosters (oh, sorry, “experts”) of modern art of the all-black-painting variety or modern architecture of the can’t-find-the-front-door variety who can’t handle Wolfe’s criticism. I also enjoyed Bonfire of the Vanities, […]

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“Using numbers to replace judgment”

Julian Marewski and Lutz Bornmann write: In science and beyond, numbers are omnipresent when it comes to justifying different kinds of judgments. Which scientific author, hiring committee-member, or advisory board panelist has not been confronted with page-long “publication manuals”, “assessment reports”, “evaluation guidelines”, calling for p-values, citation rates, h-indices, or other statistics in order to […]

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2018: How did people actually vote? (The real story, not the exit polls.)

Following up on the post that we linked to last week, here’s Yair’s analysis, using Mister P, of how everyone voted. Like Yair, I think these results are much better than what you’ll see from exit polls, partly because the analysis is more sophisticated (MRP gives you state-by-state estimates in each demographic group), partly because […]

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Hey, check this out: Columbia’s Data Science Institute is hiring research scientists and postdocs!

Here’s the official announcement: The Institute’s Postdoctoral and Research Scientists will help anchor Columbia’s presence as a leader in data-science research and applications and serve as resident experts in fostering collaborations with the world-class faculty across all schools at Columbia University. They will also help guide, plan and execute data-science research, applications and technological innovations […]

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Robustness checks are a joke

Someone pointed to this post from a couple years ago by Uri Simonsohn, who correctly wrote: Robustness checks involve reporting alternative specifications that test the same hypothesis. Because the problem is with the hypothesis, the problem is not addressed with robustness checks. Simonsohn followed up with an amusing story: To demonstrate the problem I [Simonsohn] […]

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Chocolate milk! Another stunning discovery from an experiment on 24 people!

Mike Hull writes: I was reading over this JAMA Brief Report and could not figure out what they were doing with the composite score. Here are the cliff notes: Study tested milk vs dark chocolate consumption on three eyesight performance parameters: (1) High-contrast visual acuity (2) Small-letter contrast sensitivity (3) Large-letter contrast sensitivity Only small-letter […]

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