andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-178 knowledge-graph by maker-knowledge-mining
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Introduction: Congressman Kevin Brady from Texas distributes this visualization of reformed health care in the US (click for a bigger picture): Here’s a PDF at Brady’s page, and a local copy of it. Complexity has its costs. Beyond the cost of writing it, learning it, following it, there’s also the cost of checking it. John Walker has some funny examples of what’s hidden in the almost 8000 pages of IRS code. Text mining and applied statistics will solve all that, hopefully. Anyone interested in developing a pork detection system for the legislation? Or an analysis of how much entropy to the legal code did each congressman contribute? There are already spin detectors , that help you detect whether the writer is a Democrat (“stimulus”, “health care”) or a Republican (“deficit spending”, “ObamaCare”). D+0.1: Jared Lander points to versions by Rep. Boehner and Robert Palmer .
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1 Congressman Kevin Brady from Texas distributes this visualization of reformed health care in the US (click for a bigger picture): Here’s a PDF at Brady’s page, and a local copy of it. [sent-1, score-0.999]
2 Beyond the cost of writing it, learning it, following it, there’s also the cost of checking it. [sent-3, score-0.391]
3 John Walker has some funny examples of what’s hidden in the almost 8000 pages of IRS code. [sent-4, score-0.282]
4 Text mining and applied statistics will solve all that, hopefully. [sent-5, score-0.204]
5 Anyone interested in developing a pork detection system for the legislation? [sent-6, score-0.389]
6 Or an analysis of how much entropy to the legal code did each congressman contribute? [sent-7, score-0.649]
7 There are already spin detectors , that help you detect whether the writer is a Democrat (“stimulus”, “health care”) or a Republican (“deficit spending”, “ObamaCare”). [sent-8, score-0.499]
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same-blog 1 1.0000002 178 andrew gelman stats-2010-08-03-(Partisan) visualization of health care legislation
Introduction: Congressman Kevin Brady from Texas distributes this visualization of reformed health care in the US (click for a bigger picture): Here’s a PDF at Brady’s page, and a local copy of it. Complexity has its costs. Beyond the cost of writing it, learning it, following it, there’s also the cost of checking it. John Walker has some funny examples of what’s hidden in the almost 8000 pages of IRS code. Text mining and applied statistics will solve all that, hopefully. Anyone interested in developing a pork detection system for the legislation? Or an analysis of how much entropy to the legal code did each congressman contribute? There are already spin detectors , that help you detect whether the writer is a Democrat (“stimulus”, “health care”) or a Republican (“deficit spending”, “ObamaCare”). D+0.1: Jared Lander points to versions by Rep. Boehner and Robert Palmer .
2 0.1086119 1847 andrew gelman stats-2013-05-08-Of parsing and chess
Introduction: Gary Marcus writes , An algorithm that is good at chess won’t help parsing sentences, and one that parses sentences likely won’t be much help playing chess. That is soooo true. I’m excellent at parsing sentences but I’m not so great at chess. And, worse than that, my chess ability seems to be declining from year to year. Which reminds me: I recently read Frank Brady’s much lauded Endgame , a biography of Bobby Fischer. The first few chapters were great, not just the Cinderella story of his steps to the world championship, but also the background on his childhood and the stories of the games and tournaments that he lost along the way. But after Fischer beats Spassky in 1972, the book just dies. Brady has chapter after chapter on Fisher’s life, his paranoia, his girlfriends, his travels. But, really, after the chess is over, it’s just sad and kind of boring. I’d much rather have had twice as much detail on the first part of the life and then had the post-1972 era compr
3 0.10790931 465 andrew gelman stats-2010-12-13-$3M health care prediction challenge
Introduction: i received the following press release from the Heritage Provider Network, “the largest limited Knox-Keene licensed managed care organization in California.” I have no idea what this means, but I assume it’s some sort of HMO. In any case, this looks like it could be interesting: Participants in the Health Prize challenge will be given a data set comprised of the de-identified medical records of 100,000 individuals who are members of HPN. The teams will then need to predict the hospitalization of a set percentage of those members who went to the hospital during the year following the start date, and do so with a defined accuracy rate. The winners will receive the $3 million prize. . . . the contest is designed to spur involvement by others involved in analytics, such as those involved in data mining and predictive modeling who may not currently be working in health care. “We believe that doing so will bring innovative thinking to health analytics and may allow us to solve at
4 0.093855478 693 andrew gelman stats-2011-05-04-Don’t any statisticians work for the IRS?
Introduction: A friend asks the above question and writes: This article left me thinking – how could the IRS not notice that this guy didn’t file taxes for several years? Don’t they run checks and notice if you miss a year? If I write a check our of order, there’s an asterisk next to the check number in my next bank statement showing that there was a gap in the sequence. If you ran the IRS, wouldn’t you do this: SSNs are issued sequentially. Once a SSN reaches 18, expect it to file a return. If it doesn’t, mail out a postage paid letter asking why not with check boxes such as Student, Unemployed, etc. Follow up at reasonable intervals. Eventually every SSN should be filing a return, or have an international address. Yes this is intrusive, but my goal is only to maximize tax revenue. Surely people who do this for a living could come up with something more elegant. My response: I dunno, maybe some confidentiality rules? The other thing is that I’m guessing that IRS gets lots of pushback w
5 0.091280118 239 andrew gelman stats-2010-08-28-The mathematics of democracy
Introduction: I was sent a copy of “Numbers Rule: The Vexing Mathematics of Democracy, from Plato to the Present,” by George Szpiro. It’s an interesting book that I think a lot of people will like, going over a bunch of voting paradoxes in the context of historical stories. Some of the topics (Arrow’s theorem and its recent refinements) are more interesting than others (the always nauseatingly boring (to me) of the “Alabama paradox” and various rules about which states get one extra House seat; for some reason people are always writing about this topic about which I could care less). But you can pick and choose among the chapters, so unevenness isn’t really such a problem. One thing that fascinates me about the topic of mathematics and representation is how many different ways there are to look at it. In 2002, I published a paper in Chance called Voting, Fairness, and Political Representation ( here’s a preprint version ; it later appeared, slightly revised, as a chapter in our Quantita
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same-blog 1 0.9742896 178 andrew gelman stats-2010-08-03-(Partisan) visualization of health care legislation
Introduction: Congressman Kevin Brady from Texas distributes this visualization of reformed health care in the US (click for a bigger picture): Here’s a PDF at Brady’s page, and a local copy of it. Complexity has its costs. Beyond the cost of writing it, learning it, following it, there’s also the cost of checking it. John Walker has some funny examples of what’s hidden in the almost 8000 pages of IRS code. Text mining and applied statistics will solve all that, hopefully. Anyone interested in developing a pork detection system for the legislation? Or an analysis of how much entropy to the legal code did each congressman contribute? There are already spin detectors , that help you detect whether the writer is a Democrat (“stimulus”, “health care”) or a Republican (“deficit spending”, “ObamaCare”). D+0.1: Jared Lander points to versions by Rep. Boehner and Robert Palmer .
2 0.64587986 660 andrew gelman stats-2011-04-14-Job opening at NIH for an experienced statistician
Introduction: This announcement might be of interest to some of you. The application deadline is in just a few days: The National Center for Complementary and Alternative Medicine at the National Institutes of Health is seeking an additional experienced statistician to join our Office of Clinical and Regulatory Affairs team. www.usajobs.gov is accepting applications through April 22, 2011 for the general announcement and April 21 for status (typically current federal employee) candidates. To apply to this announcement or for more information, click on the links provided below or the USAJobs link provided above and search for NIH-NCCAM-DE-11-448747 ( external ) or NIH-NCCAM-MP-11-448766 ( internal ). You have to be a U.S. citizen for this one.
3 0.64111298 465 andrew gelman stats-2010-12-13-$3M health care prediction challenge
Introduction: i received the following press release from the Heritage Provider Network, “the largest limited Knox-Keene licensed managed care organization in California.” I have no idea what this means, but I assume it’s some sort of HMO. In any case, this looks like it could be interesting: Participants in the Health Prize challenge will be given a data set comprised of the de-identified medical records of 100,000 individuals who are members of HPN. The teams will then need to predict the hospitalization of a set percentage of those members who went to the hospital during the year following the start date, and do so with a defined accuracy rate. The winners will receive the $3 million prize. . . . the contest is designed to spur involvement by others involved in analytics, such as those involved in data mining and predictive modeling who may not currently be working in health care. “We believe that doing so will bring innovative thinking to health analytics and may allow us to solve at
4 0.56802756 275 andrew gelman stats-2010-09-14-Data visualization at the American Evaluation Association
Introduction: Stephanie Evergreen writes: Media, web design, and marketing have all created an environment where stakeholders – clients, program participants, funders – all expect high quality graphics and reporting that effectively conveys the valuable insights from evaluation work. Some in statistics and mathematics have used data visualization strategies to support more useful reporting of complex ideas. Global growing interest in improving communications has begun to take root in the evaluation field as well. But as anyone who has sat through a day’s worth of a conference or had to endure a dissertation-worthy evaluation report knows, evaluators still have a long way to go. To support the development of researchers and evaluators, some members of the American Evaluation Association are proposing a new TIG (Topical Interest Group) on Data Visualization and Reporting. If you are a member of AEA (or want to be) and you are interested in joining this TIG, contact Stephanie Evergreen.
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Introduction: US National Academy of Sciences elects 84 new members (Please click through and read the whole thing.)
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1 0.93365633 1772 andrew gelman stats-2013-03-20-Stan at Google this Thurs and at Berkeley this Fri noon
Introduction: Michael Betancourt will be speaking at Google and at the University of California, Berkeley. The Google talk is closed to outsiders (but if you work at Google, you should go!); the Berkeley talk is open to all: Friday March 22, 12:10 pm, Evans Hall 1011. Title of talk: Stan : Practical Bayesian Inference with Hamiltonian Monte Carlo Abstract: Practical implementations of Bayesian inference are often limited to approximation methods that only slowly explore the posterior distribution. By taking advantage of the curvature of the posterior, however, Hamiltonian Monte Carlo (HMC) efficiently explores even the most highly contorted distributions. In this talk I will review the foundations of and recent developments within HMC, concluding with a discussion of Stan, a powerful inference engine that utilizes HMC, automatic differentiation, and adaptive methods to minimize user input. This is cool stuff. And he’ll be showing the whirlpool movie!
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Introduction: Congressman Kevin Brady from Texas distributes this visualization of reformed health care in the US (click for a bigger picture): Here’s a PDF at Brady’s page, and a local copy of it. Complexity has its costs. Beyond the cost of writing it, learning it, following it, there’s also the cost of checking it. John Walker has some funny examples of what’s hidden in the almost 8000 pages of IRS code. Text mining and applied statistics will solve all that, hopefully. Anyone interested in developing a pork detection system for the legislation? Or an analysis of how much entropy to the legal code did each congressman contribute? There are already spin detectors , that help you detect whether the writer is a Democrat (“stimulus”, “health care”) or a Republican (“deficit spending”, “ObamaCare”). D+0.1: Jared Lander points to versions by Rep. Boehner and Robert Palmer .
Introduction: Speakers: Cyrus Samii, PhD candidate, Department of Political Science, Columbia University: “Peacebuilding Policies as Quasi-Experiments: Some Examples” Macartan Humphreys, Associate Professor, Department of Political Science, Columbia University: “Sampling in developing countries: Five challenges from the field” Friday 22 Oct, 3-5pm in the Playroom (707 International Affairs Building). Open to all.
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Introduction: David Hogg pointed me to this news article by Angela Saini: It’s not often that the quiet world of mathematics is rocked by a murder case. But last summer saw a trial that sent academics into a tailspin, and has since swollen into a fevered clash between science and the law. At its heart, this is a story about chance. And it begins with a convicted killer, “T”, who took his case to the court of appeal in 2010. Among the evidence against him was a shoeprint from a pair of Nike trainers, which seemed to match a pair found at his home. While appeals often unmask shaky evidence, this was different. This time, a mathematical formula was thrown out of court. The footwear expert made what the judge believed were poor calculations about the likelihood of the match, compounded by a bad explanation of how he reached his opinion. The conviction was quashed. . . . “The impact will be quite shattering,” says Professor Norman Fenton, a mathematician at Queen Mary, University of London.
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Introduction: Michael Betancourt will be speaking at UCLA: The location for refreshment is in room 51-254 CHS at 3:00 PM. The place for the seminar is at CHS 33-105A at 3:30pm – 4:30pm, Wed 6 Mar. ["CHS" stands for Center for Health Sciences, the building of the UCLA schools of medicine and public health. Here's a map with directions .] Title of talk: Stan : Practical Bayesian Inference with Hamiltonian Monte Carlo Abstract: Practical implementations of Bayesian inference are often limited to approximation methods that only slowly explore the posterior distribution. By taking advantage of the curvature of the posterior, however, Hamiltonian Monte Carlo (HMC) efficiently explores even the most highly contorted distributions. In this talk I will review the foundations of and recent developments within HMC, concluding with a discussion of Stan, a powerful inference engine that utilizes HMC, automatic differentiation, and adaptive methods to minimize user input. This is cool stuff.
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