Blog Archives

The Most Romantic Electro-Grunge Statistical Computing Song Ever Made

February 14, 2011
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The Most Romantic Electro-Grunge Statistical Computing Song Ever Made

Warning message: This song contains highly suggestive coefficients and graphic depictions of exuberant R-core lovin’. “Plotting Ihaka” is based on Rotting Piñata by Sponge, and reflects a small measure of my boundless joy in the world of R. Despite being a firm proponent of muffins, I can confidently say that I would rather live in

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Rhythms of Equality and Inequality

February 6, 2011
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Rhythms of Equality and Inequality

Today I unveil my very first statistical YouTube video! I will do anything to keep you statisfied, and if that means YouTube, then so be it. But first, some exposition: In Panama, 10 percent of the population owned 45 percent of the income in 2000, whereas the bottom 10 percent owned only 0.6 percent. How

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Listening for trends in US baby names over 130 years

January 25, 2011
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Listening for trends in US baby names over 130 years

What happens when you mash together R‘s data crunching magic, Festival‘s speech synthesis power, and the audio wonders of the venerable music language Csound? You fall even more in love with free and open-source software, and you start hearing sounds like this: A single beat of the above sound represents the top 1000 baby names

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Dial-a-statistic! Featuring R and Estonia

January 16, 2011
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Dial-a-statistic! Featuring R and Estonia

Did you wake up this morning hoping that you would be able to listen to telephone beeps inspired by Estonian web site metrics? I knew you did! First things first: I came up with the slightly crazy idea of using the bleepy sounds that telephones make, called “dual-tone multifrequency” (DTMF) tones, as a tool in

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Newcomb, Benford, and their Dirty, Dirty Logarithms

August 22, 2010
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Newcomb, Benford, and their Dirty, Dirty Logarithms

Tom Taverner introduced me to Benford’s Law as we were eating lunch together at a statistical computing conference: If you look at the first digits of data in many naturally-occuring datasets, a startling 30 percent of them are ones. “Pah!” I said. “That belies intuition! Why would one digit occur any more than another? I’d

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