andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1189 knowledge-graph by maker-knowledge-mining
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Introduction: X pointed me to this atrocity: The data on obesity are pretty unequivocal: we’re fat, and we’re getting fatter. Explanations for this trend, however, vary widely, with the blame alternately pinned on individual behaviour, genetics and the environment. In other words, it’s a race between “we eat too much”, “we’re born that way” and “it’s society’s fault”. Now, research by Lazaros Gallos has come down strongly in favour of the third option. Gallos and his colleagues at City College of New York treated the obesity rates in some 3000 US counties as “particles” in a physical system, and calculated the correlation between pairs of “particles” as a function of the distance between them. . . . the data indicated that the size of the “obesity cities” – geographic regions with correlated obesity rates – was huge, up to 1000 km. . . . Just to be clear: I have no problem with people calculating spatial autocorrelations (or even with them using quaint terminology such as referring to coun
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1 X pointed me to this atrocity: The data on obesity are pretty unequivocal: we’re fat, and we’re getting fatter. [sent-1, score-0.416]
2 Explanations for this trend, however, vary widely, with the blame alternately pinned on individual behaviour, genetics and the environment. [sent-2, score-0.551]
3 In other words, it’s a race between “we eat too much”, “we’re born that way” and “it’s society’s fault”. [sent-3, score-0.271]
4 Now, research by Lazaros Gallos has come down strongly in favour of the third option. [sent-4, score-0.134]
5 Gallos and his colleagues at City College of New York treated the obesity rates in some 3000 US counties as “particles” in a physical system, and calculated the correlation between pairs of “particles” as a function of the distance between them. [sent-5, score-1.48]
6 the data indicated that the size of the “obesity cities” – geographic regions with correlated obesity rates – was huge, up to 1000 km. [sent-9, score-0.923]
7 Just to be clear: I have no problem with people calculating spatial autocorrelations (or even with them using quaint terminology such as referring to counties as “particles in a physical system”). [sent-13, score-1.025]
8 I do have problems with this sort of gee-whiz reporting and the leap from an autocorrelation function to “it’s society’s fault. [sent-14, score-0.426]
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Introduction: I have an optimization problem: I have a complicated physical model that predicts energy and thermal behavior of a building, given the values of a slew of parameters, such as insulation effectiveness, window transmissivity, etc. I’m trying to find the parameter set that best fits several weeks of thermal and energy use data from the real building that we modeled. (Of course I would rather explore parameter space and come up with probability distributions for the parameters, and maybe that will come later, but for now I’m just optimizing). To do the optimization, colleagues and I implemented a “particle swarm optimization” algorithm on a massively parallel machine. This involves giving each of about 120 “particles” an initial position in parameter space, then letting them move around, trying to move to better positions according to a specific algorithm. We gave each particle an initial position sampled from our prior distribution for each parameter. So far we’ve run about 140 itera
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Introduction: Hi Andrew, I came across your site while searching for blogs and posts around American obesity and wanted to reach out to get your readership’s feedback on an infographic my team built which focuses on the obesity of America and where we could end up at the going rate. If you’re interested, let’s connect. Have a great weekend! Thanks. *** I have to say, that’s pretty pitiful, to wish someone a “great weekend” on a Tuesday! This guy’s gotta ratchet up his sophistication a few notches if he ever wants to get a job as a spammer for a major software company , for example.
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Introduction: Your taxes pay for the research funding that supports the work we do here, some of which appears on this blog and almost all of which is public, free, and open-source. So, to all of the taxpayers out there in the audience: thank you.
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