andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-591 knowledge-graph by maker-knowledge-mining
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Introduction: About 12 years ago Greg Wawro, Sy Spilerman, and I started a M.A. program here in Quantitative Methods in Social Sciences, jointly between the departments of history, economics, political science, sociology, psychology, and statistics. We created a bunch of new features for the program, including an interdisciplinary course based on this book . And here’s their new logo: Don’t blame me for the pie-chart motif! Seriously, though, the program is great. I’m proud to have gotten it started, and I’m impressed by the progress that Chris Weiss and others have made in expanding the program during the past decade.
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Introduction: About 12 years ago Greg Wawro, Sy Spilerman, and I started a M.A. program here in Quantitative Methods in Social Sciences, jointly between the departments of history, economics, political science, sociology, psychology, and statistics. We created a bunch of new features for the program, including an interdisciplinary course based on this book . And here’s their new logo: Don’t blame me for the pie-chart motif! Seriously, though, the program is great. I’m proud to have gotten it started, and I’m impressed by the progress that Chris Weiss and others have made in expanding the program during the past decade.
Introduction: There’s a paradigm in applied statistics that goes something like this: 1. There is a scientific or policy question of some theoretical or practical importance. 2. Researchers gather data on relevant outcomes and perform a statistical analysis, ideally leading to a clear conclusion (p less than 0.05, or a strong posterior distribution, or good predictive performance, or high reliability and validity, whatever). 3. This conclusion informs policy. This paradigm has room for positive findings (for example, that a new program is statistically significantly better, or statistically significantly worse than what came before) or negative findings (data are inconclusive, further study is needed), even if negative findings seem less likely to make their way into the textbooks. But what happens when step 2 simply isn’t possible. This came up a few years ago—nearly 10 years ago, now!—with the excellent paper by Donohue and Wolfers which explained why it’s just about impossible to
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Introduction: Matthieu Authier writes: I just read Genetic essentialism is in our genes . Here are a few papers from Kenneth Weiss about this missing heritability problem and genetic essentialism: Evol.Ant.2011 – Weiss – Seeing the forest through the gene-trees Genetics.2011 – Weiss.&.Buchanan – Is life-law-like
4 0.13824648 2016 andrew gelman stats-2013-09-11-Zipfian Academy, A School for Data Science
Introduction: Katie Kent writes: I’m with Zipfian Academy – we’re launching next week as the first 12-week immersive program to teach data science. The program combines the hard and soft skills of data science with introductions to the data science community out here in San Francisco. The launch will be covered by a couple big tech blogs, but we’d love to offer the opportunity to blog about it to some smaller and well-respected data science blogs like yours. I don’t know anything about this but I took a look at the website and it looks pretty cool. Maybe in a future iteration of their course, they can teach Stan, once it has a few more useful features such as VB and EP.
5 0.1361278 426 andrew gelman stats-2010-11-22-Postdoc opportunity here at Columbia — deadline soon!
Introduction: The deadline for this year’s Earth Institute postdocs is 1 Dec, so it’s time to apply right away ! It’s a highly competitive interdisciplinary program, and we’ve had some statisticians in the past. We’re particularly interested in statisticians who have research interests in development and public health. It’s fine–not just fine, but ideal–if you are interested in statistical methods also.
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14 0.085967787 2048 andrew gelman stats-2013-10-03-A comment on a post at the Monkey Cage
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18 0.083021216 557 andrew gelman stats-2011-02-05-Call for book proposals
19 0.08282207 1630 andrew gelman stats-2012-12-18-Postdoc positions at Microsoft Research – NYC
20 0.080991469 185 andrew gelman stats-2010-08-04-Why does anyone support private macroeconomic forecasts?
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Introduction: About 12 years ago Greg Wawro, Sy Spilerman, and I started a M.A. program here in Quantitative Methods in Social Sciences, jointly between the departments of history, economics, political science, sociology, psychology, and statistics. We created a bunch of new features for the program, including an interdisciplinary course based on this book . And here’s their new logo: Don’t blame me for the pie-chart motif! Seriously, though, the program is great. I’m proud to have gotten it started, and I’m impressed by the progress that Chris Weiss and others have made in expanding the program during the past decade.
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Introduction: Rob Calver writes: Large and complex datasets are becoming prevalent in the social and behavioral sciences and statistical methods are crucial for the analysis and interpretation of such data. The Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences Series aims to capture new developments in statistical methodology with particular relevance to applications in the social and behavioral sciences. It seeks to promote appropriate use of statistical, econometric and psychometric methods in these applied sciences by publishing a broad range of monographs, textbooks and handbooks. The scope of the series is wide, including applications of statistical methodology in sociology, psychology, economics, education, marketing research, political science, criminology, public policy, demography, survey methodology and official statistics. The titles included in the series are designed to appeal to applied statisticians, as well as students, researchers and practitioners from the
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Introduction: Sharad Goel sends this in: Microsoft Research NYC [ http://research.microsoft.com/newyork/ ] seeks outstanding applicants for 2-year postdoctoral researcher positions. We welcome applicants with a strong academic record in one of the following areas: * Computational social science: http://research.microsoft.com/cssnyc * Online experimental social science: http://research.microsoft.com/oess_nyc * Algorithmic economics and market design: http://research.microsoft.com/algorithmic-economics/ * Machine learning: http://research.microsoft.com/mlnyc/ We will also consider applicants in other focus areas of the lab, including information retrieval, and behavioral & empirical economics. Additional information about these areas is included below. Please submit all application materials by January 11, 2013. ———- COMPUTATIONAL SOCIAL SCIENCE http://research.microsoft.com/cssnyc With an increasing amount of data on every aspect of our daily activities — from what we buy, to wh
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Introduction: A link from Tyler Cowen led me to this long blog article by Razib Khan, discussing some recent genetic findings on human origins in the context of the past twenty-five years of research and popularization of science. I don’t know much about human origins (beyond my ooh-that’s-cool reactions to exhibits at the Natural History Museum, my general statistician’s skepticism at various over-the-top claims I’ve heard over the years about “mitochondrial Eve” and the like, and various bits I’ve read over the years regarding when people came over to Australia, America, etc.), but what particularly interested me about Khan’s article was his discussion about the various controversies among scientists, his own reactions when reading and thinking about these issues as they were happening (Khan was a student at the time), and the interaction between science and political ideology. There’s a limit to how far you can go with this sort of cultural criticism of science, and Khan realizes this
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Introduction: George Leckie writes: The Centre for Multilevel Modelling is seeking to appoint two social statisticians or social scientists with advanced quantitative skills for two ESRC-funded research projects : 1. Research Assistant in Social Statistics, 1 year from 1 October 2010 2. Research Assistant/Associate in Social Statistics, 34 months from 1 October 2010.
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1 0.97120285 473 andrew gelman stats-2010-12-17-Why a bonobo won’t play poker with you
Introduction: Sciencedaily has posted an article titled Apes Unwilling to Gamble When Odds Are Uncertain : The apes readily distinguished between the different probabilities of winning: they gambled a lot when there was a 100 percent chance, less when there was a 50 percent chance, and only rarely when there was no chance In some trials, however, the experimenter didn’t remove a lid from the bowl, so the apes couldn’t assess the likelihood of winning a banana The odds from the covered bowl were identical to those from the risky option: a 50 percent chance of getting the much sought-after banana. But apes of both species were less likely to choose this ambiguous option. Like humans, they showed “ambiguity aversion” — preferring to gamble more when they knew the odds than when they didn’t. Given some of the other differences between chimps and bonobos, Hare and Rosati had expected to find the bonobos to be more averse to ambiguity, but that didn’t turn out to be the case. Thanks to Sta
2 0.96407926 837 andrew gelman stats-2011-08-04-Is it rational to vote?
Introduction: Hear me interviewed on the topic here . P.S. The interview was fine but I don’t agree with everything on the linked website. For example, this bit: Global warming is not the first case of a widespread fear based on incomplete knowledge turned out to be false or at least greatly exaggerated. Global warming has many of the characteristics of a popular delusion, an irrational fear or cause that is embraced by millions of people because, well, it is believed by millions of people! All right, then.
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Introduction: About 12 years ago Greg Wawro, Sy Spilerman, and I started a M.A. program here in Quantitative Methods in Social Sciences, jointly between the departments of history, economics, political science, sociology, psychology, and statistics. We created a bunch of new features for the program, including an interdisciplinary course based on this book . And here’s their new logo: Don’t blame me for the pie-chart motif! Seriously, though, the program is great. I’m proud to have gotten it started, and I’m impressed by the progress that Chris Weiss and others have made in expanding the program during the past decade.
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5 0.92826879 942 andrew gelman stats-2011-10-04-45% hitting, 25% fielding, 25% pitching, and 100% not telling us how they did it
Introduction: A University of Delaware press release reports : This month, the Journal of Quantitative Analysis in Sports will feature the article “An Estimate of How Hitting, Pitching, Fielding, and Base-stealing Impact Team Winning Percentages in Baseball.” In it, University of Delaware Prof. Charles Pavitt of the Department of Communication defines the perfect “formula” for Major League Baseball (MLB) teams to use to build the ultimate winning team. Pavitt found hitting accounts for more than 45 percent of teams’ winning records, fielding for 25 percent and pitching for 25 percent. And that the impact of stolen bases is greatly overestimated. He crunched hitting, pitching, fielding and base-stealing records for every MLB team over a 48-year period from 1951-1998 with a method no other researcher has used in this area. In statistical parlance, he used a conceptual decomposition of offense and defense into its component parts and then analyzed recombinations of the parts in intuitively mea
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