andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-316 knowledge-graph by maker-knowledge-mining
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Introduction: Sam Jessup writes: I am writing to ask you to recommend papers, books–anything that comes to mind that might give a prospective statistician some sense of what the future holds for statistics (and statisticians). I have a liberal arts background with an emphasis in mathematics. It seems like this is an exciting time to be a statistician, but that’s just from the outside looking in. I’m curious about your perspective on the future of the discipline. Any recommendations? My favorite is still the book, “Statistics: A Guide to the Unknown,” first edition. (I actually have a chapter in the latest (fourth) edition, but I think the first edition (from 1972, I believe) is still the best.
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4 I’m curious about your perspective on the future of the discipline. [sent-4, score-0.513]
5 My favorite is still the book, “Statistics: A Guide to the Unknown,” first edition. [sent-6, score-0.403]
6 (I actually have a chapter in the latest (fourth) edition, but I think the first edition (from 1972, I believe) is still the best. [sent-7, score-0.984]
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Introduction: Sam Jessup writes: I am writing to ask you to recommend papers, books–anything that comes to mind that might give a prospective statistician some sense of what the future holds for statistics (and statisticians). I have a liberal arts background with an emphasis in mathematics. It seems like this is an exciting time to be a statistician, but that’s just from the outside looking in. I’m curious about your perspective on the future of the discipline. Any recommendations? My favorite is still the book, “Statistics: A Guide to the Unknown,” first edition. (I actually have a chapter in the latest (fourth) edition, but I think the first edition (from 1972, I believe) is still the best.
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Introduction: Our publisher informs me of the exciting news that Amazon is now selling the 3rd edition of our book at 40% off! Enjoy.
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Introduction: The new book titled: Past, Present, and Future of Statistical Science is now available for download . The official description makes the book sound pretty stuffy: Past, Present, and Future of Statistical Science, commissioned by the Committee of Presidents of Statistical Societies (COPSS) to celebrate its 50th anniversary and the International Year of Statistics, will be published in April by Taylor & Francis/CRC Press. Through the contributions of a distinguished group of 50 statisticians, the book showcases the breadth and vibrancy of statistics, describes current challenges and new opportunities, highlights the exciting future of statistical science, and provides guidance for future statisticians. Contributors are past COPSS award honorees. But it actually has lots of good stuff, including the chapter by Tibshirani which I discussed last year (in the context of the “bet on sparsity principle”), and chapters by XL and other fun people. Also my own chapter, How do we choo
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Introduction: From a few years ago : Both the papers sent to me appear to have strong research results. Now that the research has been done, I’d recommend rewriting both articles from scratch , using the following template: 1. Start with the conclusions. Write a couple pages on what you’ve found and what you recommend. In writing these conclusions, you should also be writing some of the introduction, in that you’ll need to give enough background so that general readers can understand what you’re talking about and why they should care. But you want to start with the conclusions, because that will determine what sort of background information you’ll need to give. 2. Now step back. What is the principal evidence for your conclusions? Make some graphs and pull out some key numbers that represent your research findings which back up your claims. 3. Back one more step, now. What are the methods and data you used to obtain your research findings. 4. Now go back and write the literature review
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Introduction: Shalizi . But this one is still my favorite.
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Introduction: Sam Jessup writes: I am writing to ask you to recommend papers, books–anything that comes to mind that might give a prospective statistician some sense of what the future holds for statistics (and statisticians). I have a liberal arts background with an emphasis in mathematics. It seems like this is an exciting time to be a statistician, but that’s just from the outside looking in. I’m curious about your perspective on the future of the discipline. Any recommendations? My favorite is still the book, “Statistics: A Guide to the Unknown,” first edition. (I actually have a chapter in the latest (fourth) edition, but I think the first edition (from 1972, I believe) is still the best.
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Introduction: Geen Tomko asks: Can you recommend a good introductory book for statistical computation? Mostly, something that would help make it easier in collecting and analyzing data from student test scores. I don’t know. Usually, when people ask for a starter statistics book, my recommendation (beyond my own books) is The Statistical Sleuth. But that’s not really a computation book. ARM isn’t really a statistical computation book either. But the statistical computation books that I’ve seen don’t seems so relevant for the analyses that Tomko is looking for. For example, the R book of Venables and Ripley focuses on nonparametric statistics, which is fine but seems a bit esoteric for these purposes. Does anyone have any suggestions?
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Introduction: I was asked by Sophie Roell, an editor at The Browser , where every day they ask an expert in a field to recommend the top five books, not by them, in their subject. I was asked to recommend five books on how Americans vote. The trouble is that I’m really pretty unfamiliar with the academic literature of political science, but it seemed sort of inappropriate for a political scientist such as myself to recommend non-scholarly books that I like (for example, “Style vs. Substance” by George V. Higgins, “Lies My Teacher Told Me,” by James Loewen, “The Rascal King” by Jack Beatty, “Republican Party Reptile” by P. J. O’Rourke, and, of course, “All the King’s Men,” by Robert Penn Warren). I mean, what’s the point of that? Nobody needs me to recommend books like that. Instead, I moved sideways and asked if I could discuss five books on statistics instead. Roell said that would be fine, so I sent her a quick description, which appears below. The actual interview turned out much bett
Introduction: Remember How to Lie With Statistics? It turns out that the author worked for the cigarette companies. John Mashey points to this, from Robert Proctor’s book, “Golden Holocaust: Origins of the Cigarette Catastrophe and the Case for Abolition”: Darrell Huff, author of the wildly popular (and aptly named) How to Lie With Statistics, was paid to testify before Congress in the 1950s and then again in the 1960s, with the assigned task of ridiculing any notion of a cigarette-disease link. On March 22, 1965, Huff testified at hearings on cigarette labeling and advertising, accusing the recent Surgeon General’s report of myriad failures and “fallacies.” Huff peppered his attack with with amusing asides and anecdotes, lampooning spurious correlations like that between the size of Dutch families and the number of storks nesting on rooftops–which proves not that storks bring babies but rather that people with large families tend to have larger houses (which therefore attract more storks).
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Introduction: I used to think that fiction is about making up stories, but in recent years I’ve decided that fiction is really more of a method of telling true stories. One thing fiction allows you to do is explore what-if scenarios. I recently read two books that made me think about this: The Counterlife by Philip Roth and Things We Didn’t See Coming by Steven Amsterdam. Both books are explicitly about contingencies and possibilities: Roth’s tells a sequence of related but contradictory stories involving his Philip Roth-like (of course) protagonist, and Amsterdam’s is based on an alternative present/future. (I picture Amsterdam’s book as being set in Australia, but maybe I’m just imagining this based on my knowledge that the book was written and published in that country.) I found both books fascinating, partly because of the characters’ voices but especially because they both seemed to exemplify George Box’s dictum that to understand a system you have to perturb it. So, yes, literature an
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Introduction: Sam Jessup writes: I am writing to ask you to recommend papers, books–anything that comes to mind that might give a prospective statistician some sense of what the future holds for statistics (and statisticians). I have a liberal arts background with an emphasis in mathematics. It seems like this is an exciting time to be a statistician, but that’s just from the outside looking in. I’m curious about your perspective on the future of the discipline. Any recommendations? My favorite is still the book, “Statistics: A Guide to the Unknown,” first edition. (I actually have a chapter in the latest (fourth) edition, but I think the first edition (from 1972, I believe) is still the best.
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Introduction: James Fowler and Mark Pletcher write: Please sign up for our new study . And tell all your friends about it. Our goal is to get one million people to donate their data to science. It takes about 10 minutes to sign up, and everyone 18 and over with an internet account is eligible. Plus, once you are done, you’ll be able to see an estimate of your short-term and lifetime risk of cardiovascular disease. Just don’t do it with any fat people. I’ve heard that’s contagious . . . . Seriously, though, this looks like an interesting and fun project, and I encourage people to sign up and to tell their friends about it.
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Introduction: Alex Braunstein writes: Thanks for the post . You drove >800 pageviews to my site. That’s >90% of what Robert Scoble’s tweet generated with 184k followers, which I find incredibly impressive. 800 doesn’t sound like so much to me, but I suppose if it’s the right 800 . . .
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Introduction: Mark Palko defines a Ddulite as follows: A preference for higher tech solutions even in cases where lower tech alternatives have greater and more appropriate functionality; a person of ddulite tendencies. Though Ddulites are the opposite of Luddites with respect to attitudes toward technology, they occupy more or less the same point with respect to functionality. As a sometime Luddite myself (no cell phone, tv, microwave oven, etc.), I should in fairness point out the logic in favor of being a Ddulite. Old technology is typically pretty stable; new technology is improving. It can make sense to switch early (before the new technology actually performs better than the old) to get the benefits of being familiar with the new technology once it does take off.
Introduction: That’s the title of my talk at Montana State University this Thursday (21 Mar). For those of you who happen to be in the area, it’s 3:30-5:00pm in the Procrastinator Theater. I’m also speaking in the statistics seminar from 11-12:15 in the Byker Auditorium in the Chemistry building. Topic: Causality and Statistical Learning . P.S. My title is a bit Geng-inspired, which reminds me that I recently came across this interesting mini-bio.
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