andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1257 knowledge-graph by maker-knowledge-mining
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Introduction: From AC, AI, and AIH to WAHM, WOHM, and WM. P.S. That was all pretty pointless, so I’ll throw in this viral Jim Henson link (from the same source) for free.
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same-blog 1 1.0 1257 andrew gelman stats-2012-04-10-Statisticians’ abbreviations are even less interesting than these!
Introduction: From AC, AI, and AIH to WAHM, WOHM, and WM. P.S. That was all pretty pointless, so I’ll throw in this viral Jim Henson link (from the same source) for free.
2 0.18334363 1908 andrew gelman stats-2013-06-21-Interpreting interactions in discrete-data regression
Introduction: Mike Johns writes: Are you familiar with the work of Ai and Norton on interactions in logit/probit models? I’d be curious to hear your thoughts. Ai, C.R. and Norton E.C. 2003. Interaction terms in logit and probit models. Economics Letters 80(1): 123-129. A peer ref just cited this paper in reaction to a logistic model we tested and claimed that the “only” way to test an interaction in logit/probit regression is to use the cross derivative method of Ai & Norton. I’ve never heard of this issue or method. It leaves me wondering what the interaction term actually tests (something Ai & Norton don’t discuss) and why such an important discovery is not more widely known. Is this an issue that is of particular relevance to econometric analysis because they approach interactions from the difference-in-difference perspective? Full disclosure, I’m coming from a social science/epi background. Thus, i’m not interested in the d-in-d estimator; I want to know if any variables modify the rela
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Introduction: And we’ll throw in RStan and PyStan for free! Details here .
4 0.13190788 781 andrew gelman stats-2011-06-28-The holes in my philosophy of Bayesian data analysis
Introduction: I’ve been writing a lot about my philosophy of Bayesian statistics and how it fits into Popper’s ideas about falsification and Kuhn’s ideas about scientific revolutions. Here’s my long, somewhat technical paper with Cosma Shalizi. Here’s our shorter overview for the volume on the philosophy of social science. Here’s my latest try (for an online symposium), focusing on the key issues. I’m pretty happy with my approach–the familiar idea that Bayesian data analysis iterates the three steps of model building, inference, and model checking–but it does have some unresolved (maybe unresolvable) problems. Here are a couple mentioned in the third of the above links. Consider a simple model with independent data y_1, y_2, .., y_10 ~ N(θ,σ^2), with a prior distribution θ ~ N(0,10^2) and σ known and taking on some value of approximately 10. Inference about μ is straightforward, as is model checking, whether based on graphs or numerical summaries such as the sample variance and skewn
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Introduction: Jim Savage saw this and pointed me to this video. I didn’t actually look at it, but given that it is labeled, “For new econ Ph.D.’s about to look for a job . . . what you might expect when you give your first talk presenting your research,” I can pretty much guess what it’ll look like.
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same-blog 1 0.98163265 1257 andrew gelman stats-2012-04-10-Statisticians’ abbreviations are even less interesting than these!
Introduction: From AC, AI, and AIH to WAHM, WOHM, and WM. P.S. That was all pretty pointless, so I’ll throw in this viral Jim Henson link (from the same source) for free.
2 0.84411156 587 andrew gelman stats-2011-02-24-5 seconds of every #1 pop single
Introduction: This is pretty amazing. Now I want to hear volume 3. Also is there a way to download this as I play it so I can listen when I’m offline? P.S. Typo in title fixed. P.P.S. I originally gave a different link but was led to the apparently more definitive link above (which allows direct download) from a commenter . Thanks!
3 0.8247121 2066 andrew gelman stats-2013-10-17-G+ hangout for test run of BDA course
Introduction: Try this link . . . . OK, it worked (as well as might be expected given that we don’t have any professional audiovisual people involved). Tomorrow 8h30, I’ll post a new link with the new G+ hangout. We’ll be going through the first two sets of slides (class1a.pdf and class1b.pdf) following the link for the slides here .
4 0.80058849 1433 andrew gelman stats-2012-07-28-LOL without the CATS
Introduction: Mayo points me to this discussion [link fixed] on parsimony by philosopher Elliott Sober. I don’t really understand what he’s talking about but I am posting the link here because it might interest some of you. P.S. More discussion on this from Mayo here .
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Introduction: Xian sends along this link that might be of interest to some of you.
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Introduction: From AC, AI, and AIH to WAHM, WOHM, and WM. P.S. That was all pretty pointless, so I’ll throw in this viral Jim Henson link (from the same source) for free.
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Introduction: No joke. See here (from Kaiser Fung). At the Statistics Forum.
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Introduction: Answer here (courtesy of Kaiser Fung).
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Introduction: And we’ll throw in RStan and PyStan for free! Details here .
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Introduction: Jaakko Peltonen writes: The Seventeenth International Conference on Artificial Intelligence and Statistics (http://www.aistats.org) will be next April in Reykjavik, Iceland. AISTATS is an interdisciplinary conference at the intersection of computer science, artificial intelligence, machine learning, statistics, and related areas. ============================================================================== AISTATS 2014 Call for Papers Seventeenth International Conference on Artificial Intelligence and Statistics April 22 – 25, 2014, Reykjavik, Iceland http://www.aistats.org Colocated with a MLSS Machine Learning Summer School ============================================================================== AISTATS is an interdisciplinary gathering of researchers at the intersection of computer science, artificial intelligence, machine learning, statistics, and related areas. Since its inception in 1985, the primary goal of AISTATS has been to broaden research in the
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