andrew_gelman_stats andrew_gelman_stats-2010 andrew_gelman_stats-2010-209 knowledge-graph by maker-knowledge-mining

209 andrew gelman stats-2010-08-16-EdLab at Columbia’s Teachers’ College


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Source: html

Introduction: According to Kaiser : EdLab at Teachers’ College does a lot of interesting things, like creating technologies for the classroom and libraries, blogging, and analyzing data sets in the education sector. They’re 2 blocks from my office and I’ve never heard of them! And I even work with people at Teachers College. Columbia’s a big place. P.S. Kaiser also makes an excellent point: The most intriguing and unexpected question was: to do well in this business, do you have to read a lot? This is where I stumbled into a spaghetti carbonara analogy while mixing metaphors with the gray flannel, with which I have already been associated. Basically, statistics is not pure mathematics, there is not one correct way of doing things, there are many different methodologies, like there are hundreds of recipes for making carbonara. What statisticians do is to try many different recipes (methods), and based on tasting the food (evaluating the outcomes), we determine which recipe to use. Be


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 According to Kaiser : EdLab at Teachers’ College does a lot of interesting things, like creating technologies for the classroom and libraries, blogging, and analyzing data sets in the education sector. [sent-1, score-0.803]

2 They’re 2 blocks from my office and I’ve never heard of them! [sent-2, score-0.332]

3 Kaiser also makes an excellent point: The most intriguing and unexpected question was: to do well in this business, do you have to read a lot? [sent-7, score-0.369]

4 This is where I stumbled into a spaghetti carbonara analogy while mixing metaphors with the gray flannel, with which I have already been associated. [sent-8, score-0.894]

5 Basically, statistics is not pure mathematics, there is not one correct way of doing things, there are many different methodologies, like there are hundreds of recipes for making carbonara. [sent-9, score-0.814]

6 What statisticians do is to try many different recipes (methods), and based on tasting the food (evaluating the outcomes), we determine which recipe to use. [sent-10, score-1.265]

7 Because of this, statisticians need to be well-read, to keep up with what are the new methods being developed. [sent-11, score-0.277]

8 This is actually the kind of thing that I say–complete with a cooking example! [sent-12, score-0.242]


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Introduction: According to Kaiser : EdLab at Teachers’ College does a lot of interesting things, like creating technologies for the classroom and libraries, blogging, and analyzing data sets in the education sector. They’re 2 blocks from my office and I’ve never heard of them! And I even work with people at Teachers College. Columbia’s a big place. P.S. Kaiser also makes an excellent point: The most intriguing and unexpected question was: to do well in this business, do you have to read a lot? This is where I stumbled into a spaghetti carbonara analogy while mixing metaphors with the gray flannel, with which I have already been associated. Basically, statistics is not pure mathematics, there is not one correct way of doing things, there are many different methodologies, like there are hundreds of recipes for making carbonara. What statisticians do is to try many different recipes (methods), and based on tasting the food (evaluating the outcomes), we determine which recipe to use. Be

2 0.15083747 361 andrew gelman stats-2010-10-21-Tenure-track statistics job at Teachers College, here at Columbia!

Introduction: See below for the job announcement. It’s for Teachers College, which is about 2 blocks from the statistics department and 2 blocks from the political science department. So even though I don’t have any official connection with Teachers College (besides occasionally working with them on research projects), I very much would like to have another exciting young applied researcher here, to complement all the people we currently have in stat, poli sci, engineering, etc. In particular, we have zillions of interesting and important social science research projects going on here, and they all need statistics work. A lot of social scientists do statistics, but it’s not so easy to find a statistician who does serious social science research. All this is to say that I hope this job gets some applicants from some people who are serious about applied statistics and the development of new models and methods. Teachers College, Columbia University Department of Human Development APPLIE

3 0.13820276 222 andrew gelman stats-2010-08-21-Estimating and reporting teacher effectivenss: Newspaper researchers do things that academic researchers never could

Introduction: Alex Tabarrok reports on an analysis from the Los Angeles Times of teacher performance (as measured by so-called value-added analysis, which is basically compares teachers based on their students’ average test scores at the end of the year, after controlling for pre-test scores. It’s well known that some teachers are much better than others, but, as Alex points out, what’s striking about the L.A. Times study is that they are publishing the estimates for individual teachers . For example, this: Nice graphics, too. To me, this illustrates one of the big advantages of research in a non-academic environment. If you’re writing an article for the L.A. Times, you can do what you want (within the limits of the law). If you’re doing the same research study at a university, there are a million restrictions. For example, from an official documen t, “The primary purpose of an Institutional Review Board (IRB) is to protect the rights and welfare of human subjects participati

4 0.11878312 388 andrew gelman stats-2010-11-01-The placebo effect in pharma

Introduction: Bruce McCullough writes: The Sept 2009 issue of Wired had a big article on the increase in the placebo effect, and why it’s been getting bigger. Kaiser Fung has a synopsis . As if you don’t have enough to do, I thought you might be interested in blogging on this. My reply: I thought Kaiser’s discussion was good, especially this point: Effect on treatment group = Effect of the drug + effect of belief in being treated Effect on placebo group = Effect of belief in being treated Thus, the difference between the two groups = effect of the drug, since the effect of belief in being treated affects both groups of patients. Thus, as Kaiser puts it, if the treatment isn’t doing better than placebo, it doesn’t say that the placebo effect is big (let alone “too big”) but that the treatment isn’t showing any additional effect. It’s “treatment + placebo” vs. placebo, not treatment vs. placebo. That said, I’d prefer for Kaiser to make it clear that the additivity he’s assu

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Introduction: No joke. See here (from Kaiser Fung). At the Statistics Forum.

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Introduction: According to Kaiser : EdLab at Teachers’ College does a lot of interesting things, like creating technologies for the classroom and libraries, blogging, and analyzing data sets in the education sector. They’re 2 blocks from my office and I’ve never heard of them! And I even work with people at Teachers College. Columbia’s a big place. P.S. Kaiser also makes an excellent point: The most intriguing and unexpected question was: to do well in this business, do you have to read a lot? This is where I stumbled into a spaghetti carbonara analogy while mixing metaphors with the gray flannel, with which I have already been associated. Basically, statistics is not pure mathematics, there is not one correct way of doing things, there are many different methodologies, like there are hundreds of recipes for making carbonara. What statisticians do is to try many different recipes (methods), and based on tasting the food (evaluating the outcomes), we determine which recipe to use. Be

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Introduction: This one belongs in the statistical lexicon. Kaiser Fung nails it : In reading [news] articles, we must look out for the moment(s) when the reporters announce story time. Much of the article is great propaganda for the statistics lobby, describing an attempt to use observational data to address a practical question, sort of a Freakonomics-style application. We have no problems when they say things like: “There is a substantial gap at year’s end between students whose teachers were in the top 10% in effectiveness and the bottom 10%. The fortunate students ranked 17 percentile points higher in English and 25 points higher in math.” Or this: “On average, Smith’s students slide under his instruction, losing 14 percentile points in math during the school year relative to their peers districtwide, The Times found. Overall, he ranked among the least effective of the district’s elementary school teachers.” Midway through the article (right before the section called “Study in contras

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Introduction: Tyler Cowen links to a “scary comparison” that claims that “a one-parent family of three making $14,500 a year (minimum wage) has more disposable income than a family making $60,000 a year.” Kaiser Fung looks into this comparison in more detail. As Kaiser puts it: If we concede that the middle-income person would end up with less disposable income than the lower-income person, then we’d expect that the middle-income people will take lower-paying jobs so as to increase their disposable income. But I have not seen reports of such reverse social mobility. Theory needs to fit reality. This hole in the theory needs to be covered. This argument sounds convincing at first, but I’m not completely sure it’s right. I’d just like to expand on one of Kaiser’s other points, which is that people don’t usually have a choice between a minimum-wage job and a $60,000 job. Also, my impression is that higher-paying jobs are more pleasant than lower-paying jobs. Let me put it another w

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Introduction: I keep encountering the word “Groupon”–I think it’s some sort of pets.com-style commercial endeavor where people can buy coupons? I don’t really care, and I’ve avoided googling the word out of a general animosity toward our society’s current glorification of get-rich-quick schemes. (As you can tell, I’m still bitter about that whole stock market thing.) Anyway, even without knowing what Groupon actually is, I enjoyed this blog by Kaiser Fung in which he tries to work out some of its economic consequences. He connects the statistical notion of counterfactuals to the concept of opportunity cost from economics. The comments are interesting too.

5 0.74294019 543 andrew gelman stats-2011-01-28-NYT shills for personal DNA tests

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