andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-359 knowledge-graph by maker-knowledge-mining
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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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same-blog 1 0.99999994 359 andrew gelman stats-2010-10-21-Applied Statistics Center miniconference: Statistical sampling in developing countries
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.
Introduction: We’re doing a new thing here at the Applied Statistics Center, throwing monthly Friday afternoon mini-conferences in the Playroom (inspired by our successful miniconference on statistical consulting a couple years ago). This Friday (10 Sept), 1-5pm : Come join us this Friday, September 10th for an engaging interdisciplinary discussion of risk perception at the individual and societal level, and the role it plays in current environmental, social, and health policy debates. All are welcome! “Risk Perception in Environmental Decision-Making” Elke Weber, Columbia Business School “Cultural Cognition and the Problem of Science Communication” Dan Kahan, Yale Law School Discussants include: Michael Gerrard, Columbia Law School David Epstein, Department of Political Science, Columbia University Andrew Gelman, Department of Statistics, Columbia University
3 0.1672422 571 andrew gelman stats-2011-02-13-A departmental wiki page?
Introduction: I was recently struggling with the Columbia University philophy department’s webpage (to see who might be interested in this stuff ). The faculty webpage was horrible: it’s just a list of names and links with no information on research interests. So I did some searching on the web and found a wonderful wikipedia page which had exactly what I wanted. Then I checked my own department’s page , and it’s even worse than what they have in philosophy! (We also have this page, which is even worse in that it omits many of our faculty and has a bunch of ridiculously technical links for some of the faculty who are included.) I don’t know about the philosophy department, but the statistics department’s webpage is an overengineered mess, designed from the outset to look pretty rather than to be easily updated. Maybe we could replace it entirely with a wiki? In the meantime, if anybody feels like setting up a wikipedia entry for the research of Columbia’s statistics faculty, that
4 0.13137284 956 andrew gelman stats-2011-10-13-Hey, you! Don’t take that class!
Introduction: Back when I taught at Berkeley, I once asked a Ph.D. student how he’d decided to work with me. He said that a couple of the tenured professors had advised him not to take my class, and that this advice had got him curious: What about Bayesian statistics is so dangerous that it can scare these otherwise unflappable stat professors. Overall, my senior colleagues’ advice to students to avoid my course probably decreased my enrollment, but the students who did decide to attend surely had better character than the ones who followed directions. (Or, at least I’d like to think that.) I was reminded of that incident recently when reading a news article by Marc Tracy: A U.S. Department of Education committee is investigating whether a Columbia University department head “steered” a Jewish student away from taking a class on the Mideast taught by Professor Joseph Massad due to the perception that she would be “uncomfortable” because of the professor’s pro-Palestinian tilt . . . “Ba
5 0.11955586 866 andrew gelman stats-2011-08-23-Participate in a research project on combining information for prediction
Introduction: Thomas Wallsten writes: To viewers of Dr. Andrew Gelman’s blog, I [Wallsten] am pleased to invite you to participate in an important research project to develop improved methods for predicting future events and outcomes. More specifically, our goal is to develop methods for aggregating many individual judgments in a manner that yields more accurate predictions than any one person or small group alone could provide. Our research is funded by the Intelligence Advanced Research Project Activity (IARPA, iarpa.gov ), but its application will extend far beyond intelligence to such areas as business forecasting or medical diagnosis. Our team consists of researchers at ARA, a private company; as well as researchers at the University of Maryland-College Park, University of Michigan, Ohio State University, Fordham University, University of California-Irvine, Wake Forest University, and the University of Missouri. Details can be found at forecastingace.com/ . We are seeking to recruit ind
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same-blog 1 0.98446774 359 andrew gelman stats-2010-10-21-Applied Statistics Center miniconference: Statistical sampling in developing countries
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.
Introduction: We’re doing a new thing here at the Applied Statistics Center, throwing monthly Friday afternoon mini-conferences in the Playroom (inspired by our successful miniconference on statistical consulting a couple years ago). This Friday (10 Sept), 1-5pm : Come join us this Friday, September 10th for an engaging interdisciplinary discussion of risk perception at the individual and societal level, and the role it plays in current environmental, social, and health policy debates. All are welcome! “Risk Perception in Environmental Decision-Making” Elke Weber, Columbia Business School “Cultural Cognition and the Problem of Science Communication” Dan Kahan, Yale Law School Discussants include: Michael Gerrard, Columbia Law School David Epstein, Department of Political Science, Columbia University Andrew Gelman, Department of Statistics, Columbia University
Introduction: One thing we do here at the Applied Statistics Center is hold mini-conferences. The next one looks really cool. It’s organized by Sharad Goel and Jake Hofman (Microsoft Research, formerly at Yahoo Research), David Park (Columbia University), and Sergei Vassilvitskii (Google). As with our other conferences, one of our goals is to mix the academic and nonacademic research communities. Here’s the website for the workshop, and here’s the announcement from the organizers: With an explosion of data on every aspect of our everyday existence — from what we buy, to where we travel, to who we know — we are able to observe human behavior with granularity largely thought impossible just a decade ago. The growth of such online activity has further facilitated the design of web-based experiments, enhancing both the scale and efficiency of traditional methods. Together these advances have created an unprecedented opportunity to address longstanding questions in the social sciences, rang
4 0.76065445 1904 andrew gelman stats-2013-06-18-Job opening! Come work with us!
Introduction: Postdoctoral position in statistical modeling of social networks A full-time postdoctoral position is available beginning Fall 2014 in the research group of Tian Zheng and Andrew Gelman working on statistical analysis and modeling of social network data, in close cooperation with our experimental collaborators. Four key papers of this project so far are: http://www.stat.columbia.edu/~gelman/research/published/overdisp_final.pdf http://nersp.osg.ufl.edu/~ufruss/documents/mccormick_salganik_zheng10.pdf http://www.stat.columbia.edu/~gelman/research/published/DiPreteetal.pdf http://arxiv.org/pdf/1301.2473.pdf Requirements: The work is highly interdisciplinary, and applicants must have strong statistical and computational skills. Social science research skills are preferred but not necessary. Preferred educational background is a PhD in statistics, computer science, political science, sociology, or a related field. Expertise in Bayesian modeling and computing is required. Prev
Introduction: See below for the job announcement. It’s for Teachers College, which is about 2 blocks from the statistics department and 2 blocks from the political science department. So even though I don’t have any official connection with Teachers College (besides occasionally working with them on research projects), I very much would like to have another exciting young applied researcher here, to complement all the people we currently have in stat, poli sci, engineering, etc. In particular, we have zillions of interesting and important social science research projects going on here, and they all need statistics work. A lot of social scientists do statistics, but it’s not so easy to find a statistician who does serious social science research. All this is to say that I hope this job gets some applicants from some people who are serious about applied statistics and the development of new models and methods. Teachers College, Columbia University Department of Human Development APPLIE
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same-blog 1 0.90842539 359 andrew gelman stats-2010-10-21-Applied Statistics Center miniconference: Statistical sampling in developing countries
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.
2 0.829059 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!
3 0.77262473 1749 andrew gelman stats-2013-03-04-Stan in L.A. this Wed 3:30pm
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.
4 0.73289531 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 .
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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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