andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-1025 knowledge-graph by maker-knowledge-mining
Source: html
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
sentIndex sentText sentNum sentScore
1 Logical reasoning typically takes the following form: 1. [sent-1, score-0.108]
2 There is also a statistical version in which the above statements are replaced by averages (“A usually happens,” etc. [sent-8, score-0.158]
3 But in all these stories, the argument can fall down if you get the facts wrong. [sent-10, score-0.07]
4 Perhaps that’s one reason that statisticians can be obsessed with detail. [sent-11, score-0.11]
5 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. [sent-12, score-0.88]
6 None of those companies ranked in the top 100 companies by 1990. [sent-13, score-0.828]
7 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 point still holds. [sent-16, score-1.095]
8 This is more a comment on how a statistician such as myself will see a number and immediately feel the urge to check it. [sent-18, score-0.283]
9 If you don’t have that instinct—that feeling that numbers should directly correspond to reality—then I think you’re missing part of what it takes to really do statistics. [sent-19, score-0.391]
10 A statistician who doesn’t care about the numbers can be helpful and even make major contributions, but I still think something is missing. [sent-20, score-0.319]
11 The analogy might be a physicist who doesn’t like to tinker with machines or a chemist who doesn’t like to play around in the lab or a psychologist who has no curiosity about human motivations or an artist who doesn’t like to doodle. [sent-21, score-0.835]
12 Again, this is no criticism of Brooks—as a journalist, he’s of course more interested in good stories than in getting the details right (recall the notorious $20 dinner at Red Lobster). [sent-22, score-0.219]
13 There also might be some important part of the story that I’m missing. [sent-27, score-0.069]
14 Brooks’s column doesn’t supply a link to his data source but I’m willing to be corrected if there’s something else going on. [sent-28, score-0.282]
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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
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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
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: David Brooks writes : There’s an atmosphere of grand fragility hanging over America’s colleges. The grandeur comes from the surging application rates, the international renown, the fancy new dining and athletic facilities. The fragility comes from the fact that colleges are charging more money, but it’s not clear how much actual benefit they are providing. . . . This is an unstable situation. At some point, parents are going to decide that $160,000 is too high a price if all you get is an empty credential and a fancy car-window sticker. One part of the solution is found in three little words: value-added assessments. Colleges have to test more to find out how they’re doing. I agree with that last paragraph. Eric Loken and I said as much in the context of statistics teaching, but the principle of measuring outcomes makes sense more generally. (Issues of measurement and evaluation are particularly salient to statisticians, given that we strongly recommend formal quanti
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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
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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: Malecki asks: Is this the worst infographic ever to appear in NYT? USA Today is not something to aspire to. To connect to some of our recent themes , I agree this is a pretty horrible data display. But it’s not bad as a series of images. Considering the competition to be a cartoon or series of photos, these images aren’t so bad. One issue, I think, is that designers get credit for creativity and originality (unusual color combinations! Histogram bars shaped like mosques!) , which is often the opposite of what we want in a clear graph. It’s Martin Amis vs. George Orwell all over again.
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Introduction: Jonathan Cantor points to this poll estimating rifle-armed QB Tim Tebow as America’s favorite pro athlete: In an ESPN survey of 1,502 Americans age 12 or older, three percent identified Tebow as their favorite professional athlete. Tebow finished in front of Kobe Bryant (2 percent), Aaron Rodgers (1.9 percent), Peyton Manning (1.8 percent), and Tom Brady (1.5 percent). Amusing. What this survey says to me is that there are no super-popular athletes who are active in America today. Which actually sounds about right. No Tiger Woods, no Magic Johnson, Muhammed Ali, John Elway, Pete Rose, Billie Jean King, etc etc. Tebow is an amusing choice, people might as well pick him now while he’s still on top. As a sports celeb, he’s like Bill Lee or the Refrigerator: colorful and a solid pro athlete, but no superstar. When you think about all the colorful superstar athletes of times gone by, it’s perhaps surprising that there’s nobody out there right now to play the role. I supp
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Introduction: This is somebody’s dream job, I’m sure . . . ESPN is looking for a statistician to join the HR department as a Research Analyst . The job will consist of analytical research and producing statistics about the people that work at ESPN. Topics of interest will include productivity, efficiency, and retention of employees, among other items. In addition to data mining and producing reports, we also field surveys and analyze results. The position is located at the headquarters in Bristol, Connecticut, the same campus where nearly all ESPN shows are produced. ESPN is a Disney company, so discounts and free admission to Disney parks are available for employees. Flexible work arrangements are available, along with working in the New York City office part-time if desired. The role is a relatively new function and will have a high impact very quickly on helping the business function. Statistical software, text books, and any other resource needed to get the job done will be provided. T
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