andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-987 knowledge-graph by maker-knowledge-mining
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Introduction: This is sooooo cool. The actual statistical methods they are using are pretty crude, but that’s fine. What’s important is their focus on the important goal. It’s sort of like Bill James or Nate Silver: if you’re using good information, and you’re focused on good questions, then the fancy statistics can come later (or from others). In most educational efforts I know of (including my own), very little is done to target assessments to improvements for individual students. I really like what they’re doing here and it reminds me how I want to figure out how to do something similar in my own teaching and course materials.
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same-blog 1 1.0 987 andrew gelman stats-2011-11-02-How Khan Academy is using Machine Learning to Assess Student Mastery
Introduction: This is sooooo cool. The actual statistical methods they are using are pretty crude, but that’s fine. What’s important is their focus on the important goal. It’s sort of like Bill James or Nate Silver: if you’re using good information, and you’re focused on good questions, then the fancy statistics can come later (or from others). In most educational efforts I know of (including my own), very little is done to target assessments to improvements for individual students. I really like what they’re doing here and it reminds me how I want to figure out how to do something similar in my own teaching and course materials.
2 0.20698065 1634 andrew gelman stats-2012-12-21-Two reviews of Nate Silver’s new book, from Kaiser Fung and Cathy O’Neil
Introduction: People keep asking me what I think of Nate’s book, and I keep replying that, as a blogger, I’m spoiled. I’m so used to getting books for free that I wouldn’t go out and buy a book just for the purpose of reviewing it. (That reminds me that I should post reviews of some of those books I’ve received in the mail over the past few months.) I have, however, encountered a couple of reviews of The Signal and the Noise so I thought I’d pass them on to you. Both these reviews are by statisticians / data scientists who work here in NYC in the non-academic “real world” so in that sense they are perhaps better situated than me to review the book (also, they have not collaborated with Nate so they have no conflict of interest). Kaiser Fung gives a positive review : It is in the subtitle—“why so many predictions fail – but some don’t”—that one learns the core philosophy of Silver: he is most concerned with the honest evaluation of the performance of predictive models. The failure to look
3 0.18137936 131 andrew gelman stats-2010-07-07-A note to John
Introduction: Jeff the Productivity Sapper points me to this insulting open letter to Nate Silver written by pollster John Zogby. I’ll go through bits of Zogby’s note line by line. (Conflict of interest warning: I have collaborated with Nate and I blog on his site). Zogby writes: Here is some advice from someone [Zogby] who has been where you [Silver] are today. Sorry, John. (I can call you that, right? Since you’re calling Nate “Nate”?). Yes, you were once the hot pollster. But, no, you were never where Nate is today. Don’t kid yourself. Zogby writes: You [Nate] are hot right now – using an aggregate of other people’s work, you got 49 of 50 states right in 2008. Yes, Nate used other people’s work. That’s what’s called “making use of available data.” Or, to use a more technical term employed in statistics, it’s called “not being an idiot.” Only in the wacky world of polling are you supposed to draw inferences about the U.S.A. using only a single survey organization. I do
4 0.13758206 697 andrew gelman stats-2011-05-05-A statistician rereads Bill James
Introduction: Ben Lindbergh invited me to write an article for Baseball Prospectus. I first sent him this item on the differences between baseball and politics but he said it was too political for them. I then sent him this review of a book on baseball’s greatest fielders but he said they already had someone slotted to review that book. Then I sent him some reflections on the great Bill James and he published it ! If anybody out there knows Bill James, please send this on to him: I have some questions at the end that I’m curious about. Here’s how it begins: I read my first Bill James book in 1984, took my first statistics class in 1985, and began graduate study in statistics the next year. Besides giving me the opportunity to study with the best applied statistician of the late 20th century (Don Rubin) and the best theoretical statistician of the early 21st (Xiao-Li Meng), going to graduate school at Harvard in 1986 gave me the opportunity to sit in a basement room one evening that
5 0.13687511 364 andrew gelman stats-2010-10-22-Politics is not a random walk: Momentum and mean reversion in polling
Introduction: Nate Silver and Justin Wolfers are having a friendly blog-dispute about momentum in political polling. Nate and Justin each make good points but are also missing parts of the picture. These questions relate to my own research so I thought I’d discuss them here. There ain’t no mo’ Nate led off the discussion by writing that pundits are always talking about “momentum” in the polls: Turn on the news or read through much of the analysis put out by some of our friends, and you’re likely to hear a lot of talk about “momentum”: the term is used about 60 times per day by major media outlets in conjunction with articles about polling. When people say a particular candidate has momentum, what they are implying is that present trends are likely to perpetuate themselves into the future. Say, for instance, that a candidate trailed by 10 points in a poll three weeks ago — and now a new poll comes out showing the candidate down by just 5 points. It will frequently be said that this
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Introduction: This is sooooo cool. The actual statistical methods they are using are pretty crude, but that’s fine. What’s important is their focus on the important goal. It’s sort of like Bill James or Nate Silver: if you’re using good information, and you’re focused on good questions, then the fancy statistics can come later (or from others). In most educational efforts I know of (including my own), very little is done to target assessments to improvements for individual students. I really like what they’re doing here and it reminds me how I want to figure out how to do something similar in my own teaching and course materials.
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Introduction: Ben Lindbergh invited me to write an article for Baseball Prospectus. I first sent him this item on the differences between baseball and politics but he said it was too political for them. I then sent him this review of a book on baseball’s greatest fielders but he said they already had someone slotted to review that book. Then I sent him some reflections on the great Bill James and he published it ! If anybody out there knows Bill James, please send this on to him: I have some questions at the end that I’m curious about. Here’s how it begins: I read my first Bill James book in 1984, took my first statistics class in 1985, and began graduate study in statistics the next year. Besides giving me the opportunity to study with the best applied statistician of the late 20th century (Don Rubin) and the best theoretical statistician of the early 21st (Xiao-Li Meng), going to graduate school at Harvard in 1986 gave me the opportunity to sit in a basement room one evening that
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Introduction: Someone just stopped by and dropped off a copy of the book Wizardry: Baseball’s All-time Greatest Fielders Revealed, by Michael Humphreys. I don’t have much to say about the topic–I did see Brooks Robinson play, but I don’t remember any fancy plays. I must have seen Mark Belanger but I don’t really recall. Ozzie Smith was cool but I saw only him on TV. The most impressive thing I ever saw live was Rickey Henderson stealing a base. The best thing about that was that everyone was expecting him to steal the base, and he still was able to do it. But that wasn’t fielding either. Anyway, Humphreys was nice enough to give me a copy of his book, and since I can’t say much (I didn’t have it in me to study the formulas in detail, nor do I know enough to be able to evaluate them), I might as well say what I can say right away. (Note: Humphreys replies to some of these questions in a comment .) 1. Near the beginning, Humphreys says that 10 runs are worth about 1 win. I’ve always b
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Introduction: Jeff the Productivity Sapper points me to this insulting open letter to Nate Silver written by pollster John Zogby. I’ll go through bits of Zogby’s note line by line. (Conflict of interest warning: I have collaborated with Nate and I blog on his site). Zogby writes: Here is some advice from someone [Zogby] who has been where you [Silver] are today. Sorry, John. (I can call you that, right? Since you’re calling Nate “Nate”?). Yes, you were once the hot pollster. But, no, you were never where Nate is today. Don’t kid yourself. Zogby writes: You [Nate] are hot right now – using an aggregate of other people’s work, you got 49 of 50 states right in 2008. Yes, Nate used other people’s work. That’s what’s called “making use of available data.” Or, to use a more technical term employed in statistics, it’s called “not being an idiot.” Only in the wacky world of polling are you supposed to draw inferences about the U.S.A. using only a single survey organization. I do
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Introduction: I was recently rereading and enjoying Bill James’s Historical Baseball Abstract (the second edition, from 2001). But even the Master is not perfect. Here he is, in the context of the all-time 20th-greatest shortstop (in his reckoning): Are athletes special people? In general, no, but occasionally, yes. Johnny Pesky at 75 was trim, youthful, optimistic, and practically exploding with energy. You rarely meet anybody like that who isn’t an ex-athlete–and that makes athletes seem special. [italics in the original] Hey, I’ve met 75-year-olds like that–and none of them are ex-athletes! That’s probably because I don’t know a lot of ex-athletes. But Bill James . . . he knows a lot of athletes. He went to the bathroom with Tim Raines once! The most I can say is that I saw Rickey Henderson steal a couple bases when he was playing against the Orioles once. Cognitive psychologists talk about the base-rate fallacy , which is the mistake of estimating probabilities without accou
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Introduction: This is sooooo cool. The actual statistical methods they are using are pretty crude, but that’s fine. What’s important is their focus on the important goal. It’s sort of like Bill James or Nate Silver: if you’re using good information, and you’re focused on good questions, then the fancy statistics can come later (or from others). In most educational efforts I know of (including my own), very little is done to target assessments to improvements for individual students. I really like what they’re doing here and it reminds me how I want to figure out how to do something similar in my own teaching and course materials.
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Introduction: The last time we encountered Slate columnist Shankar Vedantam was when he puzzled over why slightly more than half of voters planned to vote for Republican candidates, given that polls show that Americans dislike the Republican Party even more than they dislike the Democrats. Vedantam attributed the new Republican majority to irrationality and “unconscious bias.” But, actually, this voting behavior is perfectly consistent with there being some moderate voters who prefer divided government. The simple, direct explanation (which Vedantam mistakenly dismisses) actually works fine. I was flipping through Slate today and noticed a new article by Vedantam headlined, “If parenthood sucks, why do we love it? Because we’re addicted.” I don’t like this one either. Vedantam starts by reviewing the evidence that people with kids are less happy than people without kids and that parents report that they are unhappy when they are around their young children. Given this, Vedantam asks
Introduction: Following up on our blog discussions a year ago, I published a review of Charles Murray’s recent book, “Coming Apart,” for the journal Statistics, Politics, and Policy. I invited Murray to publish a response, and he did so. Here’s the abstract to my review : This article examines some claims made in a recent popular book of political sociology, with the intent not being to debunk any claims but rather to connect some important social and policy positions to statistical data on income, social class, and political attitudes. The thesis of Charles Murray’s book is that America’s upper and lower classes have become increasingly separate, with elites living more disciplined, orderly lives (characterized by marriage, work, and stable families) while being largely unaware of the lifestyles of the majority of Americans. I argue that some of Murray’s conclusions are sensitive to particular choices of whom to label as elite or upper-class. From my analysis of survey data, I see the big
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Introduction: Ricardo Pietrobon writes, regarding my post from last year on attitudes toward data graphics, Wouldn’t it be the case to start formally studying the usability of graphics from a cognitive perspective? with platforms such as the mechanical turk it should be fairly straightforward to test alternative methods and come to some conclusions about what might be more informative and what might better assist in supporting decisions. btw, my guess is that these two constructs might not necessarily agree with each other. And Jessica Hullman provides some background: Measuring success for the different goals that you hint at in your article is indeed challenging, and I don’t think that most visualization researchers would claim to have met this challenge (myself included). Visualization researchers may know the user psychology well when it comes to certain dimensions of a graph’s effectiveness (such as quick and accurate responses), but I wouldn’t agree with this statement as a gene
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Introduction: Following up on our discussion the other day, Matt Buttice and Ben Highton write: It was nice to see our article mentioned and discussed by Andrew, Jeff Lax, Justin Phillips, and Yair Ghitza on Andrew’s blog in this post on Wednesday. As noted in the post, we recently published an article in Political Analysis on how well multilevel regression and poststratification (MRP) performs at producing estimates of state opinion with conventional national surveys where N≈1,500. Our central claims are that (i) the performance of MRP is highly variable, (ii) in the absence of knowing the true values, it is difficult to determine the quality of the MRP estimates produced on the basis of a single national sample, and, (iii) therefore, our views about the usefulness of MRP in instances where a researcher has a single sample of N≈1,500 are less optimistic than the ones expressed in previous research on the topic. Obviously we were interested in the blog posts. We found them stimulating
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