Posts Tagged ‘ Miscellaneous Statistics ’

Quantitative literacy is tough! Or, I had no idea that, in 1958, 96% of Americans disapproved of interracial marriage!

November 27, 2014
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Quantitative literacy is tough!  Or, I had no idea that, in 1958, 96% of Americans disapproved of interracial marriage!

Mark Palko linked to this data-rich cartoon by Randall Munroe: And I was stunned, first by the data on interracial marriage and then, retrospectively, by my earlier ignorance of these data. Was approval of interracial marriage only 4% in 1958? I had no idea. I looked it up at the Gallup site and it seems […] The post Quantitative literacy is tough! Or, I had no idea that, in 1958,…

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The hype cycle starts again

November 24, 2014
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The hype cycle starts again

Completely uncritical press coverage of a speculative analysis. But, hey, it was published in the prestigious Proceedings of the National Academy of Sciences (PPNAS)! What could possibly go wrong? Here’s what Erik Larsen writes: In a paper published in the Proceedings of the National Academy of Sciences, People search for meaning when they approach a […] The post The hype cycle starts again appeared first on Statistical Modeling, Causal Inference,…

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This is what “power = .06” looks like. Get used to it.

November 17, 2014
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This is what “power = .06” looks like.  Get used to it.

I prepared the above image for this talk. The calculations come from the second column of page 6 of this article, and the psychology study that we’re referring to is discussed here. The post This is what “power = .06” looks like. Get used ...

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“Differences Between Econometrics and Statistics” (my talk this Monday at the University of Pennsylvania econ dept)

November 9, 2014
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“Differences Between Econometrics and Statistics” (my talk this Monday at the University of Pennsylvania econ dept)

Differences Between Econometrics and Statistics:  that’s the title of the talk I’ll be giving at the econometrics workshop at noon on Monday. At 4pm in the same place, I’ll be speaking on Stan. And here are some things for people to read: For “Differences between econometrics and statistics”: Everyone’s trading bias for variance at some […] The post “Differences Between Econometrics and Statistics” (my talk this Monday at the University…

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“Differences Between Econometrics and Statistics” (my talk this Monday at the University of Pennsylvania econ dept)

November 9, 2014
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“Differences Between Econometrics and Statistics” (my talk this Monday at the University of Pennsylvania econ dept)

Differences Between Econometrics and Statistics:  that’s the title of the talk I’ll be giving at the econometrics workshop at noon on Monday. At 4pm 4:30pm in the same place, I’ll be speaking on Stan. And here are some things for people to read: For “Differences between econometrics and statistics”: Everyone’s trading bias for variance at […] The post “Differences Between Econometrics and Statistics” (my talk this Monday at the University…

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Just imagine if Ed Wegman got his hands on this program—it could do wonders for his research productivity!

November 6, 2014
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Just imagine if Ed Wegman got his hands on this program—it could do wonders for his research productivity!

Brendan Nyhan writes: I’d love to see you put some data in here that you know well and evaluate how the site handles it. The webpage in question says: Upload a data set, and the automatic statistician will attempt to describe the final column of your data in terms of the rest of the data. […] The post Just imagine if Ed Wegman got his hands on this program—it could…

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My talk today at the University of Michigan, 4pm at the Institute for Social Research

November 3, 2014
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Generalizing from sample to population Andrew Gelman, Department of Statistics, Columbia University We’ve been hearing a lot about “data” recently, but data are generally a means to an end, with the goal being to learn about some population of interest. How do we generalize from sample to population? The process seems a bit mysterious, especially […] The post My talk today at the University of Michigan, 4pm at the Institute…

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Was it really necessary to do a voting experiment on 300,000 people? Maybe 299,999 would’ve been enough? Or 299,998? Or maybe 2000?

October 30, 2014
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Was it really necessary to do a voting experiment on 300,000 people?  Maybe 299,999 would’ve been enough?  Or 299,998?  Or maybe 2000?

There’s been some discussion recently about an experiment done in Montana, New Hampshire, and California, conducted by three young political science professors, in which letters were sent to 300,000 people, in order to (possibly) affect their voting behavior. It appears that the plan was to follow up after the elections and track voter turnout. (Some […] The post Was it really necessary to do a voting experiment on 300,000 people?…

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Solution to the sample-allocation problem

October 26, 2014
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See this recent post for background. Here’s the question: You are designing an experiment where you are estimating a linear dose-response pattern with a dose that x can take on the values 1, 2, 3, and the response is continuous. Suppose that there is no systematic error and that the measurement variance is proportional to x. You […] The post Solution to the sample-allocation problem appeared first on Statistical Modeling, Causal Inference,…

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Solution to the problem on the distribution of p-values

October 25, 2014
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See this recent post for background. Here’s the question: It is sometimes said that the p-value is uniformly distributed if the null hypothesis is true. Give two different reasons why this statement is not in general true. The problem is with real examples, not just toy examples, so your reasons should not involve degenerate situations such as […] The post Solution to the problem on the distribution of p-values appeared first on…

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