andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-2107 knowledge-graph by maker-knowledge-mining
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Introduction: Mark Palko is irritated by the Times’s refusal to retract a recounting of a hoax regarding Dickens and Dostoevsky. All I can say is, the Times refuses to retract mistakes of fact that are far more current than that! See here for two examples that particularly annoyed me, to the extent that I contacted various people at the Times but ran into refusals to retract. I guess a daily newspaper publishes so much material that they can’t be expected to run a retraction every time they publish something false, even when such things are brought to their attention. Speaking of corrections, I wonder if later editions of the Samuelson economics textbook discussed their notorious graph predicting Soviet economic performance. The easiest thing would be just to remove the graph, but I think it would be a better economics lesson to discuss the error! Similarly, I think the NYT would do well to run an article on their Dickens-Dostoevsky mistake, along with a column by Arthur Brooks on how
sentIndex sentText sentNum sentScore
1 Mark Palko is irritated by the Times’s refusal to retract a recounting of a hoax regarding Dickens and Dostoevsky. [sent-1, score-0.727]
2 All I can say is, the Times refuses to retract mistakes of fact that are far more current than that! [sent-2, score-0.526]
3 See here for two examples that particularly annoyed me, to the extent that I contacted various people at the Times but ran into refusals to retract. [sent-3, score-0.4]
4 I guess a daily newspaper publishes so much material that they can’t be expected to run a retraction every time they publish something false, even when such things are brought to their attention. [sent-4, score-1.001]
5 Speaking of corrections, I wonder if later editions of the Samuelson economics textbook discussed their notorious graph predicting Soviet economic performance. [sent-5, score-0.71]
6 The easiest thing would be just to remove the graph, but I think it would be a better economics lesson to discuss the error! [sent-6, score-0.513]
7 Similarly, I think the NYT would do well to run an article on their Dickens-Dostoevsky mistake, along with a column by Arthur Brooks on how he messed up with the happiness statistics, and a column by David Brooks on how he messed up with the statistics on Jewish achievement. [sent-7, score-1.47]
8 Instead of one more column on the usual topic, why not something explaining what went wrong? [sent-8, score-0.574]
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same-blog 1 1.0 2107 andrew gelman stats-2013-11-20-NYT (non)-retraction watch
Introduction: Mark Palko is irritated by the Times’s refusal to retract a recounting of a hoax regarding Dickens and Dostoevsky. All I can say is, the Times refuses to retract mistakes of fact that are far more current than that! See here for two examples that particularly annoyed me, to the extent that I contacted various people at the Times but ran into refusals to retract. I guess a daily newspaper publishes so much material that they can’t be expected to run a retraction every time they publish something false, even when such things are brought to their attention. Speaking of corrections, I wonder if later editions of the Samuelson economics textbook discussed their notorious graph predicting Soviet economic performance. The easiest thing would be just to remove the graph, but I think it would be a better economics lesson to discuss the error! Similarly, I think the NYT would do well to run an article on their Dickens-Dostoevsky mistake, along with a column by Arthur Brooks on how
Introduction: I was thinking more about David Brooks’s anti-data column from yesterday, and I realized what is really bothering me. Brooks expresses skepticism about numbers, about the limitations of raw data, about the importance of human thinking. Fine, I agree with all of this, to some extent. But then Brooks turns around uses numbers and unquestioningly and uncritically (OK, not completely uncritically; see P.S. below). In a notorious recent case, Brooks wrote, in the context of college admissions: You’re going to want to argue with Unz’s article all the way along, especially for its narrow, math-test-driven view of merit. But it’s potentially ground-shifting. Unz’s other big point is that Jews are vastly overrepresented at elite universities and that Jewish achievement has collapsed. In the 1970s, for example, 40 percent of top scorers in the Math Olympiad had Jewish names. Now 2.5 percent do. But these numbers are incorrect, as I learned from a professor of oncology at the Univ
3 0.21051192 2280 andrew gelman stats-2014-04-03-As the boldest experiment in journalism history, you admit you made a mistake
Introduction: The pre-NYT David Brooks liked to make fun of the NYT. Here’s one from 1997 : I’m not sure I’d like to be one of the people featured on the New York Times wedding page, but I know I’d like to be the father of one of them. Imagine how happy Stanley J. Kogan must have been, for example, when his daughter Jamie got into Yale. Then imagine his pride when Jamie made Phi Beta Kappa and graduated summa cum laude. . . . he must have enjoyed a gloat or two when his daughter put on that cap and gown. And things only got better. Jamie breezed through Stanford Law School. And then she met a man—Thomas Arena—who appears to be exactly the sort of son-in-law that pediatric urologists dream about. . . . These two awesome resumes collided at a wedding ceremony . . . It must have been one of the happiest days in Stanley J. Kogan’s life. The rest of us got to read about it on the New York Times wedding page. Brooks is reputed to be Jewish himself so I think it’s ok for him to mock Jewish peop
Introduction: A Brooks op-ed in the New York Times (circulation approximately 1.5 million): People at the extremes are happier than political moderates. . . . none, it seems, are happier than the Tea Partiers . . . Jay Livingston on his blog (circulation approximately 0 (rounding to the nearest million)), giving data from the 2009-2010 General Social Survey, which is the usual place people turn to for population data on happiness of Americans: The GSS does not offer “bitter” or “Tea Party” as choices, but extreme conservatives are nearly three times as likely as others to be “not too happy.” Livingston reports that the sample size for “Extremely Conservative” here is 80. Thus the standard error for that green bar on the right is approx sqrt(0.3*0.7/80)=0.05. So how could Brooks have made such a mistake? I can think of two possibilities: 1. Brooks has some other data source that directly addresses the happiness of supporters of the Tea Party movement. 2. Brooks looked a
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Introduction: The New York Times has a feature in its Tuesday science section, Take a Number, to which I occasionally contribute (see here and here ). Today’s column , by Nicholas Balakar, is in error. The column begins: When medical researchers report their findings, they need to know whether their result is a real effect of what they are testing, or just a random occurrence. To figure this out, they most commonly use the p-value. This is wrong on two counts. First, whatever researchers might feel, this is something they’ll never know. Second, results are a combination of real effects and chance, it’s not either/or. Perhaps the above is a forgivable simplification, but I don’t think so; I think it’s a simplification that destroys the reason for writing the article in the first place. But in any case I think there’s no excuse for this, later on: By convention, a p-value higher than 0.05 usually indicates that the results of the study, however good or bad, were probably due only
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Introduction: Mark Palko is irritated by the Times’s refusal to retract a recounting of a hoax regarding Dickens and Dostoevsky. All I can say is, the Times refuses to retract mistakes of fact that are far more current than that! See here for two examples that particularly annoyed me, to the extent that I contacted various people at the Times but ran into refusals to retract. I guess a daily newspaper publishes so much material that they can’t be expected to run a retraction every time they publish something false, even when such things are brought to their attention. Speaking of corrections, I wonder if later editions of the Samuelson economics textbook discussed their notorious graph predicting Soviet economic performance. The easiest thing would be just to remove the graph, but I think it would be a better economics lesson to discuss the error! Similarly, I think the NYT would do well to run an article on their Dickens-Dostoevsky mistake, along with a column by Arthur Brooks on how
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Introduction: Logical reasoning typically takes the following form: 1. I know that A is true. 2. I know that A implies B. 3. Therefore, I can conclude that B is true. I, like Lewis Carroll, have problems with this process sometimes, but it’s pretty standard. There is also a statistical version in which the above statements are replaced by averages (“A usually happens,” etc.). But in all these stories, the argument can fall down if you get the facts wrong. Perhaps that’s one reason that statisticians can be obsessed with detail. For example, David Brooks wrote the following, in a column called “Living with Mistakes”: The historian Leslie Hannah identified the ten largest American companies in 1912. None of those companies ranked in the top 100 companies by 1990. Huh? Could that really be? I googled “ten largest american companies 1912″ and found this , from Leslie Hannah: No big deal: two still in the top 10 rather than zero in the top 100, but Brooks’s general
Introduction: I was thinking more about David Brooks’s anti-data column from yesterday, and I realized what is really bothering me. Brooks expresses skepticism about numbers, about the limitations of raw data, about the importance of human thinking. Fine, I agree with all of this, to some extent. But then Brooks turns around uses numbers and unquestioningly and uncritically (OK, not completely uncritically; see P.S. below). In a notorious recent case, Brooks wrote, in the context of college admissions: You’re going to want to argue with Unz’s article all the way along, especially for its narrow, math-test-driven view of merit. But it’s potentially ground-shifting. Unz’s other big point is that Jews are vastly overrepresented at elite universities and that Jewish achievement has collapsed. In the 1970s, for example, 40 percent of top scorers in the Math Olympiad had Jewish names. Now 2.5 percent do. But these numbers are incorrect, as I learned from a professor of oncology at the Univ
Introduction: A Brooks op-ed in the New York Times (circulation approximately 1.5 million): People at the extremes are happier than political moderates. . . . none, it seems, are happier than the Tea Partiers . . . Jay Livingston on his blog (circulation approximately 0 (rounding to the nearest million)), giving data from the 2009-2010 General Social Survey, which is the usual place people turn to for population data on happiness of Americans: The GSS does not offer “bitter” or “Tea Party” as choices, but extreme conservatives are nearly three times as likely as others to be “not too happy.” Livingston reports that the sample size for “Extremely Conservative” here is 80. Thus the standard error for that green bar on the right is approx sqrt(0.3*0.7/80)=0.05. So how could Brooks have made such a mistake? I can think of two possibilities: 1. Brooks has some other data source that directly addresses the happiness of supporters of the Tea Party movement. 2. Brooks looked a
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Introduction: The pre-NYT David Brooks liked to make fun of the NYT. Here’s one from 1997 : I’m not sure I’d like to be one of the people featured on the New York Times wedding page, but I know I’d like to be the father of one of them. Imagine how happy Stanley J. Kogan must have been, for example, when his daughter Jamie got into Yale. Then imagine his pride when Jamie made Phi Beta Kappa and graduated summa cum laude. . . . he must have enjoyed a gloat or two when his daughter put on that cap and gown. And things only got better. Jamie breezed through Stanford Law School. And then she met a man—Thomas Arena—who appears to be exactly the sort of son-in-law that pediatric urologists dream about. . . . These two awesome resumes collided at a wedding ceremony . . . It must have been one of the happiest days in Stanley J. Kogan’s life. The rest of us got to read about it on the New York Times wedding page. Brooks is reputed to be Jewish himself so I think it’s ok for him to mock Jewish peop
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Introduction: Mark Palko is irritated by the Times’s refusal to retract a recounting of a hoax regarding Dickens and Dostoevsky. All I can say is, the Times refuses to retract mistakes of fact that are far more current than that! See here for two examples that particularly annoyed me, to the extent that I contacted various people at the Times but ran into refusals to retract. I guess a daily newspaper publishes so much material that they can’t be expected to run a retraction every time they publish something false, even when such things are brought to their attention. Speaking of corrections, I wonder if later editions of the Samuelson economics textbook discussed their notorious graph predicting Soviet economic performance. The easiest thing would be just to remove the graph, but I think it would be a better economics lesson to discuss the error! Similarly, I think the NYT would do well to run an article on their Dickens-Dostoevsky mistake, along with a column by Arthur Brooks on how
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Introduction: A colleague asks: When I search the web, I find the story [of the article by Said, Wegman, et al. on social networks in climate research, which was recently bumped from the journal Computational Statistics and Data Analysis because of plagiarism] only on blogs, USA Today, and UPI. Why is that? Any idea why it isn’t reported by any of the major newspapers? Here’s my answer: 1. USA Today broke the story. Apparently this USA Today reporter put a lot of effort into it. The NYT doesn’t like to run a story that begins, “Yesterday, USA Today reported…” 2. To us it’s big news because we’re statisticians. [The main guy in the study, Edward Wegman, won the Founders Award from the American Statistical Association a few years ago.] To the rest of the world, the story is: “Obscure prof at an obscure college plagiarized an article in a journal that nobody’s ever heard of.” When a Harvard scientist paints black dots on white mice and says he’s curing cancer, that’s news. When P
Introduction: Tyler Cowen discusses his and Bryan Caplan’s reaction to that notorious book by Amy Chua, the Yale law professor who boasts of screaming at her children, calling them “garbage,” not letting them go to the bathroom when they were studying piano, etc. Caplan thinks Chua is deluded (in the sense of not being aware of research showing minimal effects of parenting on children’s intelligence and personality), foolish (in writing a book and making recommendations without trying to lean about the abundant research on child-rearing), and cruel. Cowen takes a middle view in that he doesn’t subscribe to Chua’s parenting strategies but he does think that his friends’ kids will do well (and partly because of his friends’ parenting styles, not just from their genes). Do you view yourself as special? I have a somewhat different take on the matter, an idea that’s been stewing in my mind for awhile, ever since I heard about the Wall Street Journal article that started this all. My story is
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Introduction: One of the new examples for the third edition of Bayesian Data Analysis is a spell-checking story. Here it is (just start at 2/3 down on the first page, with “Spelling correction”). I like this example—it demonstrates the Bayesian algebra, also gives a sense of the way that probability models (both “likelihood” and “prior”) are constructed from existing assumptions and data. The models aren’t just specified as a mathematical exercise, they represent some statement about reality. And the problem is close enough to our experience that we can consider ways in which the model can be criticized and improved, all in a simple example that has only three possibilities.
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Introduction: A couple years ago, upon the selection of Sarah Palin as vice-presidential nominee, I made some graphs of the popularity of governors of different-sized states: As I wrote at the time : It seems to be easier to maintain high approval in a small state. What’s going on? Some theories: in a large state, there will be more ambitious politicians on the other side, eager to knock off the incumbent governor; small states often have part-time legislatures and thus the governor is involved in less political conflict; small states (notably Alaska) tend to get more funds per capita from the federal government, and it’s easier to be popular when you can disburse more funds; large states tend to be more heterogeneous and so it’s harder to keep all the voters happy. I was curious how things have been going more recently, and Hanfei made an updated graph using data from this archive . Here’s the story: There’s lots of variation–clearly there are many other factors than state popu
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