andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-943 knowledge-graph by maker-knowledge-mining
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Introduction: Mark Palko discusses a radio interview on the effect of parents on children’s education. In short, the interviewer (Stephen Dubner of Freakonomics fame) claims that the research shows that parents don’t have much influence on whether their children go to college. The evidence is based on a comparison of adopted and non-adopted children. Palko makes a convincing case that the statistical analysis (by economist Bruce Sacerdote) doesn’t show what Dubner says it shows. I looked over the linked transcript, and overall I’m less unhappy than Palko is about the interview. I agree that some of the causal implications are sloppy, and I think it’s a bit silly for the interviewer (Kai Ryssdal) to use celebrities as a benchmark. (Ryssdal says, “if [a certain parenting style is] good enough for Steven Levitt, it’s good enough for me.” But Levitt is a multimillionaire—he’ll always have a huge financial cushion. It’s not clear that what works for him would work for others who are not so wel
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1 Mark Palko discusses a radio interview on the effect of parents on children’s education. [sent-1, score-0.369]
2 In short, the interviewer (Stephen Dubner of Freakonomics fame) claims that the research shows that parents don’t have much influence on whether their children go to college. [sent-2, score-0.454]
3 The evidence is based on a comparison of adopted and non-adopted children. [sent-3, score-0.507]
4 I looked over the linked transcript, and overall I’m less unhappy than Palko is about the interview. [sent-5, score-0.055]
5 I agree that some of the causal implications are sloppy, and I think it’s a bit silly for the interviewer (Kai Ryssdal) to use celebrities as a benchmark. [sent-6, score-0.161]
6 (Ryssdal says, “if [a certain parenting style is] good enough for Steven Levitt, it’s good enough for me. [sent-7, score-0.166]
7 ) But, taking the interview as a whole, I’m happy with its quantitative tone. [sent-10, score-0.166]
8 First, at the level of statistics and social science, it’s an interesting challenge to estimate effects of families and to try to understand the contributions of nurture and nature. [sent-14, score-0.242]
9 Second, the example interests me in the connections between the science and the politics. [sent-16, score-0.142]
10 As a conservative, Dubner is happy to see evidence confirming the idea that kids who don’t go to college, don’t go because of their genes rather than because they’re not on a college track. [sent-17, score-0.685]
11 In contrast, this sort of data won’t make Dubner so comfortable: Among the top-scoring quartile of students on the SAT: 80% of high-SES students went on to a four-year college, compared to only 44% of low-SES students. [sent-19, score-0.335]
12 Among the top-scoring students who do go to college, 80% of the high-SES kids graduate, compared to 45% of the kids of low socio-economic status. [sent-20, score-0.462]
13 Third–and this is the point I want to focus on here–this example illustrates hidden assumptions and is an excellent case to demonstrate one of my favorite tricks for understanding statistical patterns. [sent-21, score-0.121]
14 The trick is, instead of comparing A to B, compare B to A. [sent-25, score-0.082]
15 For example, “WInning the Nobel Prize adds two years to your lifespan” becomes “Not getting the Nobel Prize reduces your expected lifespan by two years. [sent-26, score-0.128]
16 What I want to focus on is: is it a good thing if children adopted into high-education families are much more likely to go to college, compared to children adopted into low-education families? [sent-31, score-1.597]
17 Taking the study’s results as correct, if you’re a child who’s adopted into a low-education family you are about 16 percentage points less likely to go to college than a kid who gets adopted into a high-education family. [sent-33, score-1.643]
18 Just for being adopted into the wrong kind of family, your chance of going to college goes down by 16%! [sent-35, score-0.674]
19 I just think this happens all the time, that people look at a comparison without thinking of it in the opposite direction. [sent-39, score-0.089]
20 I’m just using this example to illustrate the perhaps surprising benefits that can be gained by “flipping it around. [sent-43, score-0.067]
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Introduction: Mark Palko discusses a radio interview on the effect of parents on children’s education. In short, the interviewer (Stephen Dubner of Freakonomics fame) claims that the research shows that parents don’t have much influence on whether their children go to college. The evidence is based on a comparison of adopted and non-adopted children. Palko makes a convincing case that the statistical analysis (by economist Bruce Sacerdote) doesn’t show what Dubner says it shows. I looked over the linked transcript, and overall I’m less unhappy than Palko is about the interview. I agree that some of the causal implications are sloppy, and I think it’s a bit silly for the interviewer (Kai Ryssdal) to use celebrities as a benchmark. (Ryssdal says, “if [a certain parenting style is] good enough for Steven Levitt, it’s good enough for me.” But Levitt is a multimillionaire—he’ll always have a huge financial cushion. It’s not clear that what works for him would work for others who are not so wel
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: Mark Palko discusses a radio interview on the effect of parents on children’s education. In short, the interviewer (Stephen Dubner of Freakonomics fame) claims that the research shows that parents don’t have much influence on whether their children go to college. The evidence is based on a comparison of adopted and non-adopted children. Palko makes a convincing case that the statistical analysis (by economist Bruce Sacerdote) doesn’t show what Dubner says it shows. I looked over the linked transcript, and overall I’m less unhappy than Palko is about the interview. I agree that some of the causal implications are sloppy, and I think it’s a bit silly for the interviewer (Kai Ryssdal) to use celebrities as a benchmark. (Ryssdal says, “if [a certain parenting style is] good enough for Steven Levitt, it’s good enough for me.” But Levitt is a multimillionaire—he’ll always have a huge financial cushion. It’s not clear that what works for him would work for others who are not so wel
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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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