andrew_gelman_stats andrew_gelman_stats-2013 andrew_gelman_stats-2013-1692 knowledge-graph by maker-knowledge-mining
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Introduction: Stephen Dubner writes : Freakonomics Experiments is a set of simple experiments about complex issues—whether to break up with your significant other, quit your job, or start a diet, just to name a few. . . . a collaboration between researchers at the University of Chicago, Freakonomics, and—we hope!—you. Steve Levitt and John List, of the University of Chicago, run the experimental and statistical side of things. Stephen Dubner, Steve Levitt, and the Freakonomics staff have given these experiments the Freakonomics twist you’re used to. Once you flip the coin, you become a member of the most important part of the collaboration, the Freakonomics Experiments team. Without your participation, we couldn’t complete any of this research. . . . You’ll choose a question that you are facing today, such as whether to quit your job or buy a house. Then you’ll provide us some background information about yourself. After that, you’ll flip the coin to find out what you should do in your situati
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10 What the coin comes up—heads or tails—is completely random. [sent-17, score-0.411]
11 It’s a fun idea, and one thing they’ll learn is how often people say they could follow the suggested advice. [sent-19, score-0.256]
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same-blog 1 1.0 1692 andrew gelman stats-2013-01-25-Freakonomics Experiments
Introduction: Stephen Dubner writes : Freakonomics Experiments is a set of simple experiments about complex issues—whether to break up with your significant other, quit your job, or start a diet, just to name a few. . . . a collaboration between researchers at the University of Chicago, Freakonomics, and—we hope!—you. Steve Levitt and John List, of the University of Chicago, run the experimental and statistical side of things. Stephen Dubner, Steve Levitt, and the Freakonomics staff have given these experiments the Freakonomics twist you’re used to. Once you flip the coin, you become a member of the most important part of the collaboration, the Freakonomics Experiments team. Without your participation, we couldn’t complete any of this research. . . . You’ll choose a question that you are facing today, such as whether to quit your job or buy a house. Then you’ll provide us some background information about yourself. After that, you’ll flip the coin to find out what you should do in your situati
Introduction: Jonathan Cantor pointed me to a new blog post by Stephen Dubner in which he expresses disagreement with what Kaiser and I wrote in our American Scientist article , “Freakonomics: What Went Wrong?”. In response, I thought it would be interesting to go “meta” here by considering all the different ways ways that I could reply to Dubner’s criticism of our criticism of his writings. (In the same post, Dubner also slams Chris Blattman (or, as he calls him, “a man named Chris Blattman”), but I won’t get into that here.) In reacting to Dubner, I will give several perspectives, all of which I believe . Usually in writing a response, one would have to choose, but here I find it interesting to present all these different perspectives in one place. 1. Understand. I understand where Dubner is coming from. We say some positive things and some negative things about his work, but it’s natural for him to focus on the negative. I’m the same way myself, probably almost all autho
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Introduction: A friend/colleague sent me some comments on my recent article with Kaiser Fung on Freakonomics. My friend gave several reasons why he thought we were unfair to Levitt. I’ll give my reply (my friend preferred that I not quote his email, but you can get a general sense of the questions from my answers). But first let me point you to my original post, Freakonomics 2: What went wrong? , from a couple years ago, in which I raised many of the points that ultimately went into our article. And here’s my recent note. (I numbered my points, but the email I was replying to was not numbered. This is not a point-by-point rebuttal to anything but rather just a series of remarks.) 1. Both Kaiser and I are big fans of Freakonomics. It’s only because Levitt can (and has) done better, that we’re sad when he doesn’t live up to his own high standards. If we didn’t convey this sense of respect in our American Scientist article, that is our failing. 2. I think it was at best tacky and
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Introduction: Kaiser and I tell the story . Regular readers will be familiar with much of this material. We kept our article short because of space restrictions at American Scientist magazine. Now I want to do a follow-up with all the good stories that we had to cut. P.S. Let me remind everyone once again that Freakonomics (the book and the blog) has some great stuff. Kaiser and I are only picking on Levitt & co. because we know they could do so much better. P.P.S. Just to emphasize: our point that Freakonomics has mistakes is nothing new—see, for example, the articles and blogs by Felix Salmon, Ariel Rubenstein, John DiNardo, and Daniel Davies. The contribution of our new article is explore how it was that all these mistakes happened, to juxtapose the many strengths of the Freakonomics franchise (much of the work described in the first book but also a lot of what appears on their blog) with its failings. In some ways these contrasts are characteristic of social science research in
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Introduction: Responding to journalist Elizabeth Kolbert’s negative review of Freakonomics 2 in the New Yorker, Stephen Dubner writes , that, although they do not have any training in climate science, it’s also the case that: Neither of us [Levitt and Dubner] were Ku Klux Klan members either, or sumo wrestlers or Realtors or abortion providers or schoolteachers or even pimps. And yet somehow we managed to write about all that without any horse dung (well, not much at least) flying our way. But Levitt is a schoolteacher (at the University of Chicago)! And, of course, you don’t have to be a sumo wrestler to be (some kind of an) expert on sumo wrestling, nor do you have to teach in the K-12 system to be an expert in education, nor do you have to provide abortions to be an expert on abortion, etc. And Levitt has had quite a bit of horse dung thrown at him for the abortion research. The connection is that abortion and climate change matter to a lot of people, while sumo wrestling and pimps and
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Introduction: Stephen Dubner writes : Freakonomics Experiments is a set of simple experiments about complex issues—whether to break up with your significant other, quit your job, or start a diet, just to name a few. . . . a collaboration between researchers at the University of Chicago, Freakonomics, and—we hope!—you. Steve Levitt and John List, of the University of Chicago, run the experimental and statistical side of things. Stephen Dubner, Steve Levitt, and the Freakonomics staff have given these experiments the Freakonomics twist you’re used to. Once you flip the coin, you become a member of the most important part of the collaboration, the Freakonomics Experiments team. Without your participation, we couldn’t complete any of this research. . . . You’ll choose a question that you are facing today, such as whether to quit your job or buy a house. Then you’ll provide us some background information about yourself. After that, you’ll flip the coin to find out what you should do in your situati
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Introduction: Kaiser and I tell the story . Regular readers will be familiar with much of this material. We kept our article short because of space restrictions at American Scientist magazine. Now I want to do a follow-up with all the good stories that we had to cut. P.S. Let me remind everyone once again that Freakonomics (the book and the blog) has some great stuff. Kaiser and I are only picking on Levitt & co. because we know they could do so much better. P.P.S. Just to emphasize: our point that Freakonomics has mistakes is nothing new—see, for example, the articles and blogs by Felix Salmon, Ariel Rubenstein, John DiNardo, and Daniel Davies. The contribution of our new article is explore how it was that all these mistakes happened, to juxtapose the many strengths of the Freakonomics franchise (much of the work described in the first book but also a lot of what appears on their blog) with its failings. In some ways these contrasts are characteristic of social science research in
Introduction: Steven Levitt writes :. Diamond often would fall asleep in seminars, often for large chunks of time. What was amazing, however, is that he would open his eyes and then make by far the most insightful comment of the entire seminar! Now that we have n=2 [see the first part of the title of this blog entry], I’m wondering . . . maybe this sort of thing is more common than Levitt and I had realized. P.S. Levitt also writes: The one thing that puzzles me [Levitt] is why in the world would he want to be on the Board of the Federal Reserve? One thing economists just don’t understand are people’s preferences. To get meta here for a moment . . . just as Levitt can’t understand Diamond’s preferences, I find it extremely difficult to understand that Levitt is puzzled by Diamond’s desire to serve on the Federal Reserve, It’s obvious, no? Diamond has expertise on macroeconomics and, I assume, some strong and well-informed opinions on monetary policy; the Federal Reserve determ
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Introduction: Check out comment #9 here . All we need is for Steven Levitt, David Runciman, and some Reader in Management somewhere to weigh in and we’ll be all set.
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Introduction: Stephen Dubner writes : Freakonomics Experiments is a set of simple experiments about complex issues—whether to break up with your significant other, quit your job, or start a diet, just to name a few. . . . a collaboration between researchers at the University of Chicago, Freakonomics, and—we hope!—you. Steve Levitt and John List, of the University of Chicago, run the experimental and statistical side of things. Stephen Dubner, Steve Levitt, and the Freakonomics staff have given these experiments the Freakonomics twist you’re used to. Once you flip the coin, you become a member of the most important part of the collaboration, the Freakonomics Experiments team. Without your participation, we couldn’t complete any of this research. . . . You’ll choose a question that you are facing today, such as whether to quit your job or buy a house. Then you’ll provide us some background information about yourself. After that, you’ll flip the coin to find out what you should do in your situati
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Introduction: Mark Palko writes : We’ll define freshwater economics as the theory that economic behavior (and perhaps most non-economic behavior) can be explained using the concepts of rational actors and efficient markets and auteur theory as the idea that most films (particularly great films) represent the artistic vision of a single author (almost always the director) and the best way to approach one of those films is through the body of work of its author. Both of these definitions are oversimplified and a bit unfair but they will get the discussion started. . . . Compared to their nearest neighbors, film criticism and economics (particularly macroeconomics) are both difficult, messy fields. Films are collaborative efforts where individual contributions defy attribution and creative decisions often can’t be distinguished from accidents of filming. Worse yet, most films are the product of large corporations which means that dozens of VPs and executives might have played a role (sometimes
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Introduction: Bill Harris writes: On pp. 250-251 of BDA second edition, you write about multiple comparisons, and you write about stepwise regression on p. 405. How would you look at stepwise regression analyses in light of the multiple comparisons problem? Is there an issue? My reply: In this case I think the right approach is to keep all the coefs but partially pool them toward 0 (after suitable transformation). But then the challenge is coming up with a general way to construct good prior distributions. I’m still thinking about that one! Yet another approach is to put something together purely nonparametrically as with Bart.
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Introduction: A couple things in this interview by Andrew Goldman of Larry Summers currently irritated me. I’ll give the quotes and then explain my annoyance. 1. Goldman: What would the economy look like now if $1.2 trillion had been spent? Summers: I think it’s an artificial question because there would have been all kinds of problems in actually moving $1.2 trillion dollars through the system — finding enough bridge projects that were ready to go and the like. But the recovery probably would have proceeded more rapidly if the fiscal program had been larger. . . . 2. Goldman: You’re aware of — and were making light of — the fact that you occasionally rub people the wrong way. Summers: In meetings, I’m more focused on trying to figure out what the right answer is than making everybody feel validated. In Washington and at Harvard, that sometimes rubs people the wrong way. OK, now my reactions: 1. Not enough bridge projects, huh? I don’t believe it. We’ve been hearing fo
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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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