Kuang Xu writes: I’m a professor at the business school at Stanford working on operations research and statistics. Recently, I shared one of our new preprints with a friend who pointed out some of your blog posts that seem to be talking about some related phenomenon. In particular, our paper studies how, by using adaptive control, the states of a processing system are effected in such a way that congestion no longer “correlates” with the underlying slowdown of services. You mentioned in the blog where you wonder if there’s some formal treatment of this phenomenon where control removes correla ..read more

This is Jessica. Human subjects experiments are starting to appear in machine learning venues. For example, ICML, one of the big ML conferences, accepted a few papers on quantifying prediction uncertainty with user studies.   Overall, I’m glad to see this. Theoretically rigorous uncertainty approaches that provide calibration or coverage guarantees may not be worth the effort (e.g., in terms of the model retraining or holding out of additional data that they require) if providing that information doesn’t impact human decisions, or leads to under- or overreliance. We know from decades ..read more

I was reminded of the above line (it’s from a Leonard Cohen song) after reading something stupid on the internet regarding some technical issue, and various people were trying to place the dispute in the context of a so-called academic “war.” I won’t get into the details because there are a million such arguments on the internet, and here I want to focus on a general problem in communication that this example illustrates. I’ve been involved in lots of academic disagreements over the years, and I pretty much never think it’s a good idea to frame any of them as a “war,” even as a joke. Indeed, I ..read more

Word on the street I often hear people say things like “We do MCMC to get a full representation of the posterior.” Their intuition seems to be that MCMC is going to take a set of draws that covers the posterior in some way. Misleading textbook examples I’m just as guilty of this as everyone else. The textbook examples are in 1D or 2D. We throw darts at a unit square and keep the ones in an inscribed circle to calculate pi, for example, or we sample independently form a 1D distribution and fill in a histogram (in the limit of infinitely many draws and infinitesimal bins, the histogram approache ..read more

From Ray Monk’s biography of Bertrand Russell: Though the Russells were not especially wealthy, they employed—as was common in Britain until after the Second World War—a number of servants: a cook, a housemaid, a gardener, a chauffeur and a nanny. Arguably this is not so much different than modern society: even if we who live in comfortable circumstances do not employ personal servants, we still benefit from the labor of thousands of people working in farms, factories, and everything in between. What struck me about the above story regarding Russell is not so much that he had all these serva ..read more

Greg Sargent writes: I disagree with Sargent’s statement that “The reason Trump regularly tells lies that are very easy to debunk . . . is to assert the power to say what truth is.” I think it’s simpler than that. People like to say things that make them look better, and this is easier to do if you’re not constrained by the truth. The big question is not so much why someone who has lied a lot in the past keeps lying—people typically keep doing with what’s worked for them before—but rather why so many of his supporters don’t seem to mind. And there I’d like to draw a connection to something ..read more

Elden Griggs writes: I have been grading a homework problem where the students have come to two different conclusions. The question was: You want to gather data to determine which of two students is a better basketball shooter. You plan to have each student take N shots and then compare their shooting percentages. Roughly how large does N have to be for you to have a good chance of distinguishing a 30% shooter from a 40% shooter? Essentially, there were two sets of student answers. The first set simulated and found the answer to be around 120-130 depending how they rounded (generally they w ..read more

Thomas Hühn writes: I’m thinking about doing a Bayesian analysis of a very small subset of PISA or TIMSS data. Those large-scale education surveys do not report students achievement scores as single numbers, but they report five or ten numbers, so called plausible values. Those plausible values have been sampled from a constructed probability distribution. The user guides and methodology papers strongly warn against taking those five plausible values as five observations, and also against taking the mean of those five plausible values and doing statistical analysis on that. Instead you’re sup ..read more

Roger Critchlow points us to this post from Jürgen Schmidhuber, “How 3 Turing Awardees Republished Key Methods and Ideas Whose Creators They Failed to Credit.” The whole thing is too long and detailed to follow—it’s like one of those pieces of outsider art with scribblings all over the margins of an elaborate painting on an already-patterned fabric—but I did follow one of the links in the post which pointed to this: This reminds me of Stan’s pedantic mode where it gives a warning if you do something like define a variable named sigma without constraining it to be positive or if you assign a ..read more

A Beatles fan pointed me to this news item from a few years ago, “A Songwriting Mystery Solved: Math Proves John Lennon Wrote ‘In My Life.'” This surprised me, because in his memoir, Many Years from Now, Paul McCartney very clearly stated that he, Paul, wrote it. Also, the news report is from NPR. Who you gonna trust, NPR or Paul McCartney? The question pretty much answers itself. But I was curious, so I read on: Over the years, Lennon and McCartney have revealed who really wrote what, but some songs are still up for debate. The two even debate between themselves — their memories seem to diff ..read more