andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-827 knowledge-graph by maker-knowledge-mining
Source: html
Introduction: We’re all familiar with the gee-whiz style of science and technology writing in which hardly a day dawns without a cure for cancer, or a new pollution-free energy source, or some other amazing breakthrough. We don’t always get the privilege of seeing such reporting shot down the moment it hits the presses. Here’s journalist Matthew Philips: What does it take for an idea to spread from one to many? For a minority opinion to become the majority belief? According to a new study by scientists at the Rensselaer Polytechnic Institute, the answer is 10%. Once 10% of a population is committed to an idea, it’s inevitable that it will eventually become the prevailing opinion of the entire group. The key is to remain committed. . . . The research actually validates the entrenched strategy of the handful of House Republicans threatening to sink John Boehner‘s budget proposal. Turns out if you’re in the minority, you have less of an incentive to compromise than the majority does. Because if
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1 We’re all familiar with the gee-whiz style of science and technology writing in which hardly a day dawns without a cure for cancer, or a new pollution-free energy source, or some other amazing breakthrough. [sent-1, score-0.09]
2 We don’t always get the privilege of seeing such reporting shot down the moment it hits the presses. [sent-2, score-0.249]
3 Here’s journalist Matthew Philips: What does it take for an idea to spread from one to many? [sent-3, score-0.137]
4 For a minority opinion to become the majority belief? [sent-4, score-0.602]
5 According to a new study by scientists at the Rensselaer Polytechnic Institute, the answer is 10%. [sent-5, score-0.164]
6 Once 10% of a population is committed to an idea, it’s inevitable that it will eventually become the prevailing opinion of the entire group. [sent-6, score-0.787]
7 The research actually validates the entrenched strategy of the handful of House Republicans threatening to sink John Boehner‘s budget proposal. [sent-11, score-0.602]
8 Turns out if you’re in the minority, you have less of an incentive to compromise than the majority does. [sent-12, score-0.354]
9 Because if you stick to your guns, and reach that crucial 10%, your ideas eventually win out. [sent-13, score-0.275]
10 This is dumber than dumb, as is revealed in the very first comment to the post: But what happens when 10 percent of a population holds one opinion, and another 10 percent hold the opposite view? [sent-14, score-0.779]
11 It reminds me of a puzzle book that I read when I was a kid. [sent-17, score-0.078]
12 One of the puzzles was: What happens when an irresistible force meets an immovable object? [sent-18, score-0.943]
13 I thought and thought and couldn’t figure it out, so I flipped to the end of the book. [sent-19, score-0.093]
14 The answer: It is not possible for an irresistible force and an immovable object to exist in the same universe, thus the question makes no sense. [sent-20, score-0.817]
15 By the way, this is a rare (perhaps) case in which the research was misrepresented not just by the journalist but by the researchers themselves. [sent-21, score-0.24]
16 Here’s the very first sentence from the RPI press release : Scientists at Rensselaer Polytechnic Institute have found that when just 10 percent of the population holds an unshakable belief, their belief will always be adopted by the majority of the society. [sent-22, score-0.908]
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same-blog 1 0.99999988 827 andrew gelman stats-2011-07-28-Amusing case of self-defeating science writing
Introduction: We’re all familiar with the gee-whiz style of science and technology writing in which hardly a day dawns without a cure for cancer, or a new pollution-free energy source, or some other amazing breakthrough. We don’t always get the privilege of seeing such reporting shot down the moment it hits the presses. Here’s journalist Matthew Philips: What does it take for an idea to spread from one to many? For a minority opinion to become the majority belief? According to a new study by scientists at the Rensselaer Polytechnic Institute, the answer is 10%. Once 10% of a population is committed to an idea, it’s inevitable that it will eventually become the prevailing opinion of the entire group. The key is to remain committed. . . . The research actually validates the entrenched strategy of the handful of House Republicans threatening to sink John Boehner‘s budget proposal. Turns out if you’re in the minority, you have less of an incentive to compromise than the majority does. Because if
2 0.095837586 1269 andrew gelman stats-2012-04-19-Believe your models (up to the point that you abandon them)
Introduction: In a discussion of his variant of the write-a-thousand-words-a-day strategy (as he puts it, “a system for the production of academic results in writing”), Thomas Basbøll writes : Believe the claims you are making. That is, confine yourself to making claims you believe. I always emphasize this when I [Basbøll] define knowledge as “justified, true belief”. . . . I think if there is one sure way to undermine your sense of your own genius it is to begin to say things you know to be publishable without being sure they are true. Or even things you know to be “true” but don’t understand well enough to believe. He points out that this is not so easy: In times when there are strong orthodoxies it can sometimes be difficult to know what to believe. Or, rather, it is all too easy to know what to believe (what the “right belief” is). It is therefore difficult to stick to statements of one’s own belief. I sometimes worry that our universities, which are systems of formal education and for
3 0.094295144 972 andrew gelman stats-2011-10-25-How do you interpret standard errors from a regression fit to the entire population?
Introduction: David Radwin asks a question which comes up fairly often in one form or another: How should one respond to requests for statistical hypothesis tests for population (or universe) data? I [Radwin] first encountered this issue as an undergraduate when a professor suggested a statistical significance test for my paper comparing roll call votes between freshman and veteran members of Congress. Later I learned that such tests apply only to samples because their purpose is to tell you whether the difference in the observed sample is likely to exist in the population. If you have data for the whole population, like all members of the 103rd House of Representatives, you do not need a test to discern the true difference in the population. Sometimes researchers assume some sort of superpopulation like “all possible Congresses” or “Congresses across all time” and that the members of any given Congress constitute a sample. In my current work in education research, it is sometimes asserted t
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Introduction: An interview with me from 2012 : You’re a statistician and wrote a book, Red State, Blue State, Rich State, Poor State , looking at why Americans vote the way they do. In an election year I think it would be a good time to revisit that question, not just for people in the US, but anyone around the world who wants to understand the realities – rather than the stereotypes – of how Americans vote. I regret the title I gave my book. I was too greedy. I wanted it to be an airport bestseller because I figured there were millions of people who are interested in politics and some subset of them are always looking at the statistics. It’s got a very grabby title and as a result people underestimated the content. They thought it was a popularisation of my work, or, at best, an expansion of an article we’d written. But it had tons of original material. If I’d given it a more serious, political science-y title, then all sorts of people would have wanted to read it, because they would
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Introduction: The other day on the sister blog we discussed a recent Pew Research survey that seemed to show that Republicans are becoming more partisan about evolution (or, as Paul Krugman put it, “So what happened after 2009 that might be driving Republican views? . . . Republicans are being driven to identify in all ways with their tribe — and the tribal belief system is dominated by anti-science fundamentalists”). We presented some discussion and evidence from Dan Kahan suggesting that the evidence for such a change was not so clear at all. Kahan drew his conclusions from a more detailed analysis of the much-discussed Pew data, along with a comparison to a recent Gallup poll. Also following up on this is sociologist David Wealiem, who pulls some more data into the discussion: Although the Pew report mentions only the 2009 survey, the question has been asked a number of times since 2005. Here are the results—the numbers represent the percent saying “evolved” minus the percent sayin
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Introduction: We’re all familiar with the gee-whiz style of science and technology writing in which hardly a day dawns without a cure for cancer, or a new pollution-free energy source, or some other amazing breakthrough. We don’t always get the privilege of seeing such reporting shot down the moment it hits the presses. Here’s journalist Matthew Philips: What does it take for an idea to spread from one to many? For a minority opinion to become the majority belief? According to a new study by scientists at the Rensselaer Polytechnic Institute, the answer is 10%. Once 10% of a population is committed to an idea, it’s inevitable that it will eventually become the prevailing opinion of the entire group. The key is to remain committed. . . . The research actually validates the entrenched strategy of the handful of House Republicans threatening to sink John Boehner‘s budget proposal. Turns out if you’re in the minority, you have less of an incentive to compromise than the majority does. Because if
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Introduction: After our discussion of the sad case of Darrell Huff, the celebrated “How to Lie with Statistics” guy who had a lucrative side career disparaging the link between smoking and cancer, I was motivated to follow John Mashey’s recommendation and read the book, Golden Holocaust: Origins of the Cigarette Catastrophe and the Case for Abolition, by historian Robert Proctor. My first stop upon receiving the book was the index, in particular the entry for Rubin, Donald B. I followed the reference to pages 440-442 and found the description of Don’s activities to be accurate, neither diminished nor overstated, to the best of my knowledge. Rubin is the second-most-famous statistician to have been paid by the cigarette industry, but several other big and small names have been on the payroll at one time or another. Here’s a partial list . Just including the people I know or have heard of: Herbert Solomon, Stanford Richard Tweedie, Bond U Arnold Zellner, U of Chicago Paul Switzer, S
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Introduction: Ed Glaeser writes : The late Senator Daniel Patrick Moynihan of New York is often credited with saying that the way to create a great city is to “create a great university and wait 200 years,” and the body of evidence on the role that universities play in generating urban growth continues to grow. I’ve always thought this too, that it’s too bad that, given the total cost, a lot more cities would’ve benefited, over the years, by maintaining great universities rather than building expensive freeways, RenCens, and so forth. But Joseph Delaney argues the opposite , considering the case of New Haven, home of what is arguably the second-best university in the country (I assume Glaeser would agree with me on this one): According to wikipedia, the poverty rate in New Haven is 24%, which compares unfavorably with the rest of the United States where it is 14%. The poverty rate in New Haven, despite the presence of Yale, is nearly twice that of the United States as a whole. Now,
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Introduction: David Hogg sends in this bizarre bit of news reporting by Robert Evans: Until now, in the four decades since it was first posited, no one has convincingly claimed to have glimpsed the Higgs Boson, let alone proved that it actually exists. At an eagerly awaited briefing on Tuesday at the CERN research centre near Geneva, two independent teams of “Higgs Hunters” – a term they themselves hate – were widely expected to suggest they were fairly confident they had spotted it. But not confident enough, in the physics world of ultra-precision where certainty has to be measured at nothing less than 100 percent, to announce “a discovery.” In the jargon, this level is described as 5 sigma . . . So far, so good. But then comes this doozy: As one scientist explained, that level of accuracy would equate to the 17th-century discoverer of gravity, Isaac Newton, sitting under his apple tree and a million apples one after another falling on his head without one missing. Huh? A free
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Introduction: Mark Chaves sent me this great article on religion and religious practice: After reading a book or article in the scientific study of religion, I [Chaves] wonder if you ever find yourself thinking, “I just don’t believe it.” I have this experience uncomfortably often, and I think it’s because of a pervasive problem in the scientific study of religion. I want to describe that problem and how to overcome it. The problem is illustrated in a story told by Meyer Fortes. He once asked a rainmaker in a native culture he was studying to perform the rainmaking ceremony for him. The rainmaker refused, replying: “Don’t be a fool, whoever makes a rain-making ceremony in the dry season?” The problem is illustrated in a different way in a story told by Jay Demerath. He was in Israel, visiting friends for a Sabbath dinner. The man of the house, a conservative rabbi, stopped in the middle of chanting the prayers to say cheerfully: “You know, we don’t believe in any of this. But then in Judai
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Introduction: This is my last entry derived from Anthony Burgess’s book reviews , and it’ll be short. His review of Angus Wilson’s “The Strange Ride of Rudyard Kipling: His Life and Works” is a wonderfully balanced little thing. Nothing incredibly deep–like most items in the collection, the review is only two pages long–but I give it credit for being a rare piece of Kipling criticism I’ve seen that (a) seriously engages with the politics, without (b) congratulating itself on bravely going against the fashions of the politically incorrect chattering classes by celebrating Kipling’s magnificent achievement blah blah blah. Instead, Burgess shows respect for Kipling’s work and puts it in historical, biographical, and literary context. Burgess concludes that Wilson’s book “reminds us, in John Gross’s words, that Kipling ‘remains a haunting, unsettling presence, with whom we still have to come to terms.’ Still.” Well put, and generous of Burgess to end his review with another’s quote. Other cri
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Introduction: I was talking with June Williamson and mentioned offhand that I’d seen something in the paper saying that if only we’d invested a few billion dollars in levees we would’ve saved zillions in economic damage from the flood. (A quick search also revealed this eerily prescient article from last month and, more recently, this online discussion.) June said, No, no, no: levees are not the way to go: Here and here are the articles on “soft infrastructure” for the New York-New Jersey Harbor I was mentioning, summarizing work that is more extensively published in two books, “Rising Currents” and “On the Water: Palisade Bay”: The hazards posed by climate change, sea level rise, and severe storm surges make this the time to transform our coastal cities through adaptive design. The conventional response to flooding, in recent history, has been hard engineering — fortifying the coastal infrastructure with seawalls and bulkheads to protect real estate at the expense of natural t
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Introduction: We’re all familiar with the gee-whiz style of science and technology writing in which hardly a day dawns without a cure for cancer, or a new pollution-free energy source, or some other amazing breakthrough. We don’t always get the privilege of seeing such reporting shot down the moment it hits the presses. Here’s journalist Matthew Philips: What does it take for an idea to spread from one to many? For a minority opinion to become the majority belief? According to a new study by scientists at the Rensselaer Polytechnic Institute, the answer is 10%. Once 10% of a population is committed to an idea, it’s inevitable that it will eventually become the prevailing opinion of the entire group. The key is to remain committed. . . . The research actually validates the entrenched strategy of the handful of House Republicans threatening to sink John Boehner‘s budget proposal. Turns out if you’re in the minority, you have less of an incentive to compromise than the majority does. Because if
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Introduction: Jessy, Aki, and I write : We review the Akaike, deviance, and Watanabe-Akaike information criteria from a Bayesian perspective, where the goal is to estimate expected out-of-sample-prediction error using a bias-corrected adjustment of within-sample error. We focus on the choices involved in setting up these measures, and we compare them in three simple examples, one theoretical and two applied. The contribution of this review is to put all these information criteria into a Bayesian predictive context and to better understand, through small examples, how these methods can apply in practice. I like this paper. It came about as a result of preparing Chapter 7 for the new BDA . I had difficulty understanding AIC, DIC, WAIC, etc., but I recognized that these methods served a need. My first plan was to just apply DIC and WAIC on a couple of simple examples (a linear regression and the 8 schools) and leave it at that. But when I did the calculations, I couldn’t understand the resu
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Introduction: Aki and I write : The Watanabe-Akaike information criterion (WAIC) and cross-validation are methods for estimating pointwise out-of-sample prediction accuracy from a fitted Bayesian model. WAIC is based on the series expansion of leave-one-out cross-validation (LOO), and asymptotically they are equal. With finite data, WAIC and cross-validation address different predictive questions and thus it is useful to be able to compute both. WAIC and an importance-sampling approximated LOO can be estimated directly using the log-likelihood evaluated at the posterior simulations of the parameter values. We show how to compute WAIC, IS-LOO, K-fold cross-validation, and related diagnostic quantities in the Bayesian inference package Stan as called from R. This is important, I think. One reason the deviance information criterion (DIC) has been so popular is its implementation in Bugs. We think WAIC and cross-validation make more sense than DIC, especially from a Bayesian perspective in whic
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