andrew_gelman_stats andrew_gelman_stats-2012 andrew_gelman_stats-2012-1173 knowledge-graph by maker-knowledge-mining
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Introduction: Karl Broman writes : I [Karl] personally would avoid sports entirely, as I view the subject to be insufficiently serious. . . . Certainly lots of statisticians are interested in sports. . . . And I’m not completely uninterested in sports: I like to watch football, particularly Nebraska, Green Bay, and Baltimore, and to see Notre Dame or any team from Florida or Texas lose. But statistics about sports? Yawn. As a person who loves sports, statistics, and sports statistics, I have a few thoughts: 1. Not everyone likes sports, and even fewer are interested in any particular sport. It’s ok to use sports examples, but don’t delude yourself into thinking that everyone in the class cares about it. 2. Don’t forget foreign students. A lot of them don’t even know the rules of kickball, fer chrissake! 3. Of the students who care about a sport, there will be a minority who really care. We had some serious basketball fans in our class last year. 4. I think the best solution
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1 Karl Broman writes : I [Karl] personally would avoid sports entirely, as I view the subject to be insufficiently serious. [sent-1, score-0.752]
2 As a person who loves sports, statistics, and sports statistics, I have a few thoughts: 1. [sent-12, score-0.747]
3 Not everyone likes sports, and even fewer are interested in any particular sport. [sent-13, score-0.219]
4 It’s ok to use sports examples, but don’t delude yourself into thinking that everyone in the class cares about it. [sent-14, score-0.943]
5 Of the students who care about a sport, there will be a minority who really care. [sent-19, score-0.279]
6 We had some serious basketball fans in our class last year. [sent-20, score-0.197]
7 I think the best solution is to cover examples in all sorts of topics, including but not limited to sports. [sent-22, score-0.26]
8 I’ve been trying to work in more examples from areas such as cooking, sewing, and shopping. [sent-23, score-0.188]
9 In my experience, students looove education examples, stories about grades, studying, and so forth. [sent-25, score-0.382]
10 But maybe that’s just at the sorts of colleges where I’ve taught: Columbia, Harvard, Berkeley, Chicago. [sent-26, score-0.136]
11 Perhaps students at less elite institutions are less interested in grades. [sent-27, score-0.294]
12 Getting back to Karl’s point about sports being unimportant: Yeah, I pretty much agree with him on that one. [sent-29, score-0.675]
13 Psychologists and economists who study sports will make the claim that the research has larger value, for example in studying decision making or in isolating some cognitive process (as in the justly-celebrated “hot-hand” study), but ultimately I think sports are valuable for their own sake. [sent-30, score-1.592]
14 Sports are a form of art, it’s not a topic such as medicine or education that has much interest beyond itself. [sent-31, score-0.171]
15 That’s ok, though, as long as we’re honest about it, and as long as we also include examples that interest other students in the class. [sent-32, score-0.495]
16 Whenever you teach an applied example well, you induce some subject-matter learning. [sent-34, score-0.271]
17 When I teach sex ratios of births, I give the probability as 0. [sent-35, score-0.29]
18 When I teach a sports example, students learn a bit about sports and psychology (for example, the hot hand). [sent-38, score-1.839]
19 I have no interest in teaching students the rules of craps or the probability of getting three of a kind in a poker hand. [sent-40, score-0.562]
20 There are lots of probability examples out there that have the same level of complexity but apply to real-world situations. [sent-41, score-0.275]
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same-blog 1 0.99999994 1173 andrew gelman stats-2012-02-17-Sports examples in class
Introduction: Karl Broman writes : I [Karl] personally would avoid sports entirely, as I view the subject to be insufficiently serious. . . . Certainly lots of statisticians are interested in sports. . . . And I’m not completely uninterested in sports: I like to watch football, particularly Nebraska, Green Bay, and Baltimore, and to see Notre Dame or any team from Florida or Texas lose. But statistics about sports? Yawn. As a person who loves sports, statistics, and sports statistics, I have a few thoughts: 1. Not everyone likes sports, and even fewer are interested in any particular sport. It’s ok to use sports examples, but don’t delude yourself into thinking that everyone in the class cares about it. 2. Don’t forget foreign students. A lot of them don’t even know the rules of kickball, fer chrissake! 3. Of the students who care about a sport, there will be a minority who really care. We had some serious basketball fans in our class last year. 4. I think the best solution
Introduction: Hey, we all know the answer: “correlation does not imply causation”—but of course life is more complicated than that. As philosophers, economists, statisticians, and others have repeatedly noted, most of our information about the world is observational not experimental, yet we manage to draw causal conclusions all the time. Sure, some of these conclusions are wrong (more often than 5% of the time, I’m sure) but that’s an accepted part of life. Challenges in this regard arise in the design of a study, in the statistical analysis, in how you write it up for a peer-reviewed journal, and finally in how you present it to the world. School sports and life outcomes An interesting case of all this came up recently in a post on Freakonomics that pointed to a post on Deadspin that pointed to a research article . The claim was that “sports participation [in high school] causes women to be less likely to be religious . . . more likely to have children . . . more likely to be singl
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Introduction: Gur Yaari writes : Anyone who has ever watched a sports competition is familiar with expressions like “on fire”, “in the zone”, “on a roll”, “momentum” and so on. But what do these expressions really mean? In 1985 when Thomas Gilovich, Robert Vallone and Amos Tversky studied this phenomenon for the first time, they defined it as: “. . . these phrases express a belief that the performance of a player during a particular period is significantly better than expected on the basis of the player’s overall record”. Their conclusion was that what people tend to perceive as a “hot hand” is essentially a cognitive illusion caused by a misperception of random sequences. Until recently there was little, if any, evidence to rule out their conclusion. Increased computing power and new data availability from various sports now provide surprising evidence of this phenomenon, thus reigniting the debate. Yaari goes on to some studies that have found time dependence in basketball, baseball, voll
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Introduction: Alex Chernavsky writes: I recently came across an interesting blog post , written by someone who is self-taught in statistics (not that there’s anything wrong with that). I have no particular expertise in statistics, but her analysis looks impressive to me. I’d be very interested to find out the opinion of a professional statistician. Do you have any interest in blogging about this subject? My (disappointing, I’m sure) reply: This indeed looks interesting. I don’t have the time/energy to look at it more right now, and it’s too far from any areas of my expertise for me to give any kind of quick informed opinion. It would be good for this sort of discussion to appear in a nutrition journal where the real experts could get at it. I expect there are some strong statisticians who work in that field, although I don’t really know for sure. P.S. I suppose I really should try to learn more about this sort of thing, as it could well affect my life more than a lot of other subje
5 0.18364564 2243 andrew gelman stats-2014-03-11-The myth of the myth of the myth of the hot hand
Introduction: Phil pointed me to this paper so I thought I probably better repeat what I wrote a couple years ago: 1. The effects are certainly not zero. We are not machines, and anything that can affect our expectations (for example, our success in previous tries) should affect our performance. 2. The effects I’ve seen are small, on the order of 2 percentage points (for example, the probability of a success in some sports task might be 45% if you’re “hot” and 43% otherwise). 3. There’s a huge amount of variation, not just between but also among players. Sometimes if you succeed you will stay relaxed and focused, other times you can succeed and get overconfidence. 4. Whatever the latest results on particular sports, I can’t see anyone overturning the basic finding of Gilovich, Vallone, and Tversky that players and spectators alike will perceive the hot hand even when it does not exist and dramatically overestimate the magnitude and consistency of any hot-hand phenomenon that does exist.
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Introduction: Karl Broman writes : I [Karl] personally would avoid sports entirely, as I view the subject to be insufficiently serious. . . . Certainly lots of statisticians are interested in sports. . . . And I’m not completely uninterested in sports: I like to watch football, particularly Nebraska, Green Bay, and Baltimore, and to see Notre Dame or any team from Florida or Texas lose. But statistics about sports? Yawn. As a person who loves sports, statistics, and sports statistics, I have a few thoughts: 1. Not everyone likes sports, and even fewer are interested in any particular sport. It’s ok to use sports examples, but don’t delude yourself into thinking that everyone in the class cares about it. 2. Don’t forget foreign students. A lot of them don’t even know the rules of kickball, fer chrissake! 3. Of the students who care about a sport, there will be a minority who really care. We had some serious basketball fans in our class last year. 4. I think the best solution
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Introduction: Frontiers of Science is a course offered as part of Columbia University’s Core Curriculum. The course is controversial, with some people praising its overview of several areas of science, and others feeling that a more traditional set of introductory science courses would do the job better. Last month, the faculty in charge of the course wrote the following public letter : The United States is in the midst of a debate over the value of a traditional college education. Why enroll in a place like Columbia College when you can obtain an undergraduate degree for $10,000 or learn everything from Massive Open Online Courses? In more parochial terms, what is the value added by approaches such as Columbia’s Core Curriculum? Recently students in our Core Course, Frontiers of Science (FoS), provided a partial answer. The FoS faculty designed a survey to gauge the scientific skills and knowledge of the Class of 2016 both before and after taking FoS. In an assembly held during orientati
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Introduction: Dan Kahan writes: Okay, have done due diligence here & can’t find the reference. It was in recent blog — and was more or less an aside — but you ripped into researchers (pretty sure econometricians, but this could be my memory adding to your account recollections it conjured from my own experience) who purport to make estimates or predictions based on multivariate regression in which the value of particular predictor is set at some level while others “held constant” etc., on ground that variance in that particular predictor independent of covariance in other model predictors is unrealistic. You made it sound, too, as if this were one of the pet peeves in your menagerie — leading me to think you had blasted into it before. Know what I’m talking about? Also — isn’t this really just a way of saying that the model is misspecified — at least if the goal is to try to make a valid & unbiased estimate of the impact of that particular predictor? The problem can’t be that one is usin
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Introduction: Aurelian Muntean writes: I have read an article on NPR and the journal article that spun this news. What draw my attention was the discussion in terms of causation implied by one of the authors of the article interviewed in the NPR news, and also by the conclusions of the article itself claiming large effects. Although the total sample (self-selecting pregnant women) seems very large (85,176) the subsamples (270 out of which 114 were in the sub-subsample revealing statistically significant association) used to support the analysis seem to be too small. Or not? My response: The different sources of information do seem to be in some conflict: - The JAMA article reports the autism rate of 1 per 1000 for children of mothers taking folic acid and 2 per 1000 for children of mothers not taking folic acid. (They also report the adjusted odds ratio as 0.6 rather than 0.5, indicted that the two groups differ a bit in some background variables.) - The NPR article has this q
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Introduction: Karl Broman writes : I [Karl] personally would avoid sports entirely, as I view the subject to be insufficiently serious. . . . Certainly lots of statisticians are interested in sports. . . . And I’m not completely uninterested in sports: I like to watch football, particularly Nebraska, Green Bay, and Baltimore, and to see Notre Dame or any team from Florida or Texas lose. But statistics about sports? Yawn. As a person who loves sports, statistics, and sports statistics, I have a few thoughts: 1. Not everyone likes sports, and even fewer are interested in any particular sport. It’s ok to use sports examples, but don’t delude yourself into thinking that everyone in the class cares about it. 2. Don’t forget foreign students. A lot of them don’t even know the rules of kickball, fer chrissake! 3. Of the students who care about a sport, there will be a minority who really care. We had some serious basketball fans in our class last year. 4. I think the best solution
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Introduction: Bob told me the other day (the other week, actually, as I’m stacking up posts here with a roughly one-month delay) that I shouldn’t try to compete with the electrical engineers when it comes to length of C.V.: according to Bob, these dudes can have over two thousand publications! How do they do it? First, an EE prof will have tons of graduate students and postdocs, they’re all writing papers and presenting at conferences, and they all stick his name on the author list. Second, these students and postdocs write up and publish every experiment they do . Including (especially!) computer experiments. And . . . all these people writing paper cite each other, so they quickly rack up thousands of citations. Upon hearing this, my first reaction to this was fear, plain and simple. One of the distinguishing characteristics of my own research record is that I have so many publications and citations. Those electrical engineers . . . how dare they go around devaluing my currency!
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