andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1782 knowledge-graph by maker-knowledge-mining
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Introduction: Ben Hansen recommended to me this book and course by Daniel Kaplan. It looks pretty good. I’ve only looked at the website, not the book itself, and I’m sure I’d find lots of places to disagree with it on details, but the general flow seemed reasonable, also I liked that there’s lots of course materials to go with it. Does anyone have any experience with this book? Is it the way to go (for now)?
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2 I’ve only looked at the website, not the book itself, and I’m sure I’d find lots of places to disagree with it on details, but the general flow seemed reasonable, also I liked that there’s lots of course materials to go with it. [sent-3, score-2.984]
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same-blog 1 0.99999994 1782 andrew gelman stats-2013-03-30-“Statistical Modeling: A Fresh Approach”
Introduction: Ben Hansen recommended to me this book and course by Daniel Kaplan. It looks pretty good. I’ve only looked at the website, not the book itself, and I’m sure I’d find lots of places to disagree with it on details, but the general flow seemed reasonable, also I liked that there’s lots of course materials to go with it. Does anyone have any experience with this book? Is it the way to go (for now)?
2 0.19982049 1642 andrew gelman stats-2012-12-28-New book by Stef van Buuren on missing-data imputation looks really good!
Introduction: Ben points us to a new book, Flexible Imputation of Missing Data . It’s excellent and I highly recommend it. Definitely worth the $89.95. Van Buuren’s book is great even if you don’t end up using the algorithm described in the book (I actually like their approach but I do think there are some limitations with their particular implementation, which is one reason we’re developing our own package ); he supplies lots of intuition, examples, and graphs. P.S. Stef’s book features an introduction by Don Rubin, which gets me thinking: if Don can find the time to write an introduction to somebody else’s book, he surely should be willing to read and comment on the third edition of his own book, no?
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Introduction: Details here .
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Introduction: X marks the spot . I’ll post the slides soon (not just for the students in my class; these should be helpful for anyone teaching Bayesian data analysis from our book ). But I don’t think you’ll get much from reading the slides alone; you’ll get more out of the book (or, of course, from taking the class).
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Introduction: Eoin Lawless wrote me: I’ve been reading your blog (and John Kruschke ‘s) for several months now, as a result of starting to learn Bayesian methods from Doing Bayesian Data Analysis [I love the title of that book! --- ed.]. More recently I completed a Coursera course on Data Science. I found learning through the medium of a online course to be an amazing experience. It does not replace books, but learning new material at the same time as other people and discussing it in the forums is very motivational. Additionally it is much easier to work through exercises and projects when there is a deadline and some element of competition than to plow through the end of chapter exercises in a book. This is especially true, I believe, when the learning is for a long term goal, rather than to be used immediately in work, for example. My question: you are obviously evangelical about the benefits that Bayesian statistics brings, have you ever considered producing a Coursera (or similar) cour
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same-blog 1 0.98964995 1782 andrew gelman stats-2013-03-30-“Statistical Modeling: A Fresh Approach”
Introduction: Ben Hansen recommended to me this book and course by Daniel Kaplan. It looks pretty good. I’ve only looked at the website, not the book itself, and I’m sure I’d find lots of places to disagree with it on details, but the general flow seemed reasonable, also I liked that there’s lots of course materials to go with it. Does anyone have any experience with this book? Is it the way to go (for now)?
Introduction: Ben points us to a new book, Flexible Imputation of Missing Data . It’s excellent and I highly recommend it. Definitely worth the $89.95. Van Buuren’s book is great even if you don’t end up using the algorithm described in the book (I actually like their approach but I do think there are some limitations with their particular implementation, which is one reason we’re developing our own package ); he supplies lots of intuition, examples, and graphs. P.S. Stef’s book features an introduction by Don Rubin, which gets me thinking: if Don can find the time to write an introduction to somebody else’s book, he surely should be willing to read and comment on the third edition of his own book, no?
3 0.86558884 31 andrew gelman stats-2010-05-13-Visualization in 1939
Introduction: Willard Cope Brinton’s second book Graphic Presentation (1939) surprised me with the quality of its graphics. Prof. Michael Stoll has some scans at Flickr . For example: The whole book can be downloaded (in a worse resolution) from Archive.Org .
4 0.86311686 1179 andrew gelman stats-2012-02-21-“Readability” as freedom from the actual sensation of reading
Introduction: In her essay on Margaret Mitchell and Gone With the Wind, Claudia Roth Pierpoint writes: The much remarked “readability” of the book must have played a part in this smooth passage from the page to the screen, since “readability” has to do not only with freedom from obscurity but, paradoxically, with freedom from the actual sensation of reading [emphasis added]—of the tug and traction of words as they move thoughts into place in the mind. Requiring, in fact, the least reading, the most “readable” book allows its characters to slip easily through nets of words and into other forms. Popular art has been well defined by just this effortless movement from medium to medium, which is carried out, as Leslie Fiedler observed in relation to Uncle Tom’s Cabin, “without loss of intensity or alteration of meaning.” Isabel Archer rises from the page only in the hanging garments of Henry James’s prose, but Scarlett O’Hara is a free woman. Well put. I wish Pierpoint would come out with ano
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Introduction: I happened to come across a little book, “Current Glossary: Words Coined Since the War.” Here are some of them: as’pi-rin, n. A white compound used as a drug in the cure of headaches and rheumatism. bob’go, n. A kind of antelope in Africa; its meat is good for food. cat’ta-lo, n. A cross between an American bison and a cow. dart, n. A short, pointed spear-like weapon of steel dropped by airmen in attacks on the enemy. free’lance, n. A rover in literature, a writer not in the employ of one firm. griz’zly bear. A new kind of dance. You get the idea. P.S. Some more literary nostalgia from the archives: Prolefeed 70 Years of Best Sellers More on book sales . . . and reflections on the disappearance of millions of copies of the once-ubiquitous “Alive!”
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same-blog 1 0.96718431 1782 andrew gelman stats-2013-03-30-“Statistical Modeling: A Fresh Approach”
Introduction: Ben Hansen recommended to me this book and course by Daniel Kaplan. It looks pretty good. I’ve only looked at the website, not the book itself, and I’m sure I’d find lots of places to disagree with it on details, but the general flow seemed reasonable, also I liked that there’s lots of course materials to go with it. Does anyone have any experience with this book? Is it the way to go (for now)?
Introduction: Here’s a good one if you want to tell your students about question wording bias. It’s fun because the data are all on the web–the research is something that students could do on their own–if they know what to look for. Another win for Google. Here’s the story. I found the following graph on the front page of the American Enterprise Institute, a well-known D.C. think tank: My first thought was that they should replace this graph by a time series, which would show so much more information. I did a web search and, indeed, looking at a broad range of poll questions over time gives us a much richer perspective on public opinion about Afghanistan than is revealed in the above graph. I did a quick google search (“polling report afghanistan”) and found this . The quick summary is that roughly 40% of Americans favor the Afghan war (down from about 50% from 2006 through early 2009). The Polling Report page also features the Quninipiac poll featured in the above graph; here it r
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Introduction: A student I’m working with writes: I was planning on getting a applied stat text as a desk reference, and for that I’m assuming you’d recommend your own book. Also, being an economics student, I was initially planning on doing my analysis in STATA, but I noticed on your blog that you use R, and apparently so does the rest of the statistics profession. Would you rather I do my programming in R this summer, or does it not matter? It doesn’t look too hard to learn, so just let me know what’s most convenient for you. My reply: Yes, I recommend my book with Jennifer Hill. Also the book by John Fox, An R and S-plus Companion to Applied Regression, is a good way to get into R. I recommend you use both Stata and R. If you’re already familiar with Stata, then stick with it–it’s a great system for working with big datasets. You can grab your data in Stata, do some basic manipulations, then save a smaller dataset to read into R (using R’s read.dta() function). Once you want to make fu
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Introduction: I received an email with the above title from Daniel Adkins, who elaborates: I [Adkins] am having a tough time with a dataset including 40K obs and 8K subjects. Trying to estimate a 2 level logit with random intercept and age slope and about 13 fixed covariates. I have tried several R packages (lme4, lme4a, glmmPQL, MCMCglmm) and stata xtmelogit and gllamm to no avail. xtmelogit crashes from insufficient memory. The R packages yield false convergences. A simpler model w/ random intercept only gives stable estimates in lme4 with a very large number of quadrature point (nAGQ>220). When i try this (nAGQ=221) with the random age term, it doesn’t make it through a single iteration in 72 hours (have tried both w/ and w/out RE correlation). I am using a power desktop that is top of the line compared to anything other than a cluster. Have tried start values for fixed effects in lme4 and that doesn’t help (couldn’t figure out how to specify RE starts). Do you have any advice. Should I move t
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Introduction: A student in my intro class came by the other day with a lot of questions. It soon became clear that he was confused about a lot of things, going back several weeks in the course. What this means is that we did not do a good job of monitoring his performance earlier during the semester. But the question now is: what do do next? I’ll sign the drop form any time during the semester, but he didn’t want to drop the class (the usual scheduling issues). And he doesn’t want to get a C or a D. He’s in big trouble and at this point is basically rolling the dice that he’ll do well enough on the final to eke out a B in the course. (Yes, he goes to section meetings and office hours, and he even tried hiring a tutor. But it’s tough–if you’ve already been going to class and still don’t know what’s going on, it’s not so easy to pull yourself out of the hole, even if you have a big pile of practice problems ahead of you.) What we really need for this student, and others like him, is a road
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