andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-108 knowledge-graph by maker-knowledge-mining
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Introduction: A NY Times Environment blog entry summarizes an article in Proceedings of the National Academy of Sciences that looks into whether there really is a “scientific consensus” that humans are substantially changing the climate. There is. That’s pretty much “dog bites man” as far as news is concerned. But although the results of the study don’t seem noteworthy, I was struck by this paragraph in the blog writeup, which is pretty much a quote of the PNAS article: For example, of the top 50 climate researchers identified by the study (as ranked by the number of papers they had published), only 2 percent fell into the camp of climate dissenters. Of the top 200 researchers, only 2.5 percent fell into the dissenter camp. That is consistent with past work, including opinion polls, suggesting that 97 to 98 percent of working climate scientists accept the evidence for human-induced climate change. Two percent of the top 50, that’s one person. And 2.5 percent of the top 200, that’s five
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1 A NY Times Environment blog entry summarizes an article in Proceedings of the National Academy of Sciences that looks into whether there really is a “scientific consensus” that humans are substantially changing the climate. [sent-1, score-0.388]
2 That’s pretty much “dog bites man” as far as news is concerned. [sent-3, score-0.21]
3 That is consistent with past work, including opinion polls, suggesting that 97 to 98 percent of working climate scientists accept the evidence for human-induced climate change. [sent-7, score-1.095]
4 As a general rule, when the numerator in count data is very small, or when the denominator is fairly small, I prefer to see the numerator and denominator separately rather than a percentage. [sent-11, score-0.986]
5 If someone says “this guy has been making more than 80% of his free throws this post season,” I want to know if that is 6/7 or 17/20. [sent-12, score-0.253]
6 So I think they should say 1/50 and 5/200, rather than 2% of the top 50 and 2. [sent-13, score-0.374]
7 Yes, I understand these are mathematically identical, but I betcha a lot of people see “2% of 50″ and don’t realize that’s one person, even though they’d realize it if they thought about it for just a second. [sent-15, score-0.379]
8 By the way, one guy (I assume it’s a guy, most of them are guys) has over 850 climate-related publications. [sent-16, score-0.214]
9 Fourteen people have over 500 publications each (one of these is the “dissenter” among the top 50). [sent-17, score-0.447]
10 Andrew might attain this sort of level if he keeps up as his current rate, but for most of the rest of us this is ridiculous. [sent-19, score-0.194]
11 Quite a selection effect, too: it’d be pretty much impossible to be considered as one of their “top 50″ climate experts if you are under 45 years old. [sent-20, score-0.594]
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same-blog 1 1.0000001 108 andrew gelman stats-2010-06-24-Sometimes the raw numbers are better than a percentage
Introduction: A NY Times Environment blog entry summarizes an article in Proceedings of the National Academy of Sciences that looks into whether there really is a “scientific consensus” that humans are substantially changing the climate. There is. That’s pretty much “dog bites man” as far as news is concerned. But although the results of the study don’t seem noteworthy, I was struck by this paragraph in the blog writeup, which is pretty much a quote of the PNAS article: For example, of the top 50 climate researchers identified by the study (as ranked by the number of papers they had published), only 2 percent fell into the camp of climate dissenters. Of the top 200 researchers, only 2.5 percent fell into the dissenter camp. That is consistent with past work, including opinion polls, suggesting that 97 to 98 percent of working climate scientists accept the evidence for human-induced climate change. Two percent of the top 50, that’s one person. And 2.5 percent of the top 200, that’s five
Introduction: My friend Seth, whom I know from Berkeley (we taught a course together on left-handedness), has a blog on topics ranging from thoughtful discussions of scientific evidence, to experiences with his unconventional weight-loss scheme, offbeat self-experimentation, and advocacy of fringe scientific theories, leavened with occasional dollops of cynicism and political extremism . I agree with Seth on some things but not others. ( Here’s Seth’s reason for not attempting a clinical trial of his diet.) Recently I was disturbed (but, I’m sorry to say, not surprised) to see Seth post the following: Predictions of climate models versus reality . I [Seth] have only seen careful prediction-vs-reality comparisons made by AGW [anthropogenic global warming] skeptics. Those who believe humans are dangerously warming the planet appear to be silent on this subject. In response, Phil commented : Funny, on the day you [Seth] made your post saying that you haven’t seen comparis
Introduction: We had a discussion the other day of a paper, “The Economic Effects of Climate Change,” by economist Richard Tol. The paper came to my attention after I saw a notice from Adam Marcus that it was recently revised because of data errors. But after looking at the paper more carefully, I see a bunch of other problems that, to me, make the whole analysis close to useless as it stands. I think this is worth discussing because the paper has been somewhat influential (so far cited 328 times, according to Google Scholar) and has even been cited in the popular press as evidence that “Climate change has done more good than harm so far and is likely to continue doing so for most of this century . . . There are many likely effects of climate change: positive and negative, economic and ecological, humanitarian and financial. And if you aggregate them all, the overall effect is positive today — and likely to stay positive until around 2080. That was the conclusion of Professor Richard Tol
Introduction: The other day we discussed that paper on ovulation and voting (you may recall that the authors reported a scattered bunch of comparisons, significance tests, and p-values, and I recommended that they would’ve done better to simply report complete summaries of their data, so that readers could see the comparisons of interest in full context), and I was thinking a bit more about why I was so bothered that it was published in Psychological Science, which I’d thought of as a serious research journal. My concern isn’t just that that the paper is bad—after all, lots of bad papers get published—but rather that it had nothing really going for it, except that it was headline bait. It was a survey done on Mechanical Turk, that’s it. No clever design, no clever questions, no care in dealing with nonresponse problems, no innovative data analysis, no nothing. The paper had nothing to offer, except that it had no obvious flaws. Psychology is a huge field full of brilliant researchers.
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Introduction: A NY Times Environment blog entry summarizes an article in Proceedings of the National Academy of Sciences that looks into whether there really is a “scientific consensus” that humans are substantially changing the climate. There is. That’s pretty much “dog bites man” as far as news is concerned. But although the results of the study don’t seem noteworthy, I was struck by this paragraph in the blog writeup, which is pretty much a quote of the PNAS article: For example, of the top 50 climate researchers identified by the study (as ranked by the number of papers they had published), only 2 percent fell into the camp of climate dissenters. Of the top 200 researchers, only 2.5 percent fell into the dissenter camp. That is consistent with past work, including opinion polls, suggesting that 97 to 98 percent of working climate scientists accept the evidence for human-induced climate change. Two percent of the top 50, that’s one person. And 2.5 percent of the top 200, that’s five
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Introduction: Tapen Sinha writes: Living in Mexico, I have been witness to many strange (and beautiful) things. Perhaps the strangest happened during the first outbreak of A(H1N1) in Mexico City. We had our university closed, football (soccer) was played in empty stadiums (or should it be stadia) because the government feared a spread of the virus. The Metro was operating and so were the private/public buses and taxis. Since the university was closed, we took the opportunity to collect data on facemask use in the public transport systems. It was a simple (but potentially deadly!) exercise in first hand statistical data collection that we teach our students (Although I must admit that I did not dare sending my research assistant to collect data – what if she contracted the virus?). I believe it was a unique experiment never to be repeated. The paper appeared in the journal Health Policy. From the abstract: At the height of the influenza epidemic in Mexico City in the spring of 2009, the f
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