hamilton

11 ms·

61.
by hamilton 17y ago
Thanks to liebke for posting this, and Bradford for writing it. I have two points. First, your point about programming is incredibly important. I've worked with people who had amazing insights about statistical problems, but went cross-eye
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by hamilton 17y ago
Having lived across the street from the Delancey St. Foundation for a while, I've had the privilege of enjoying their many services. Deeply impressive organization. If you ever find yourself in the SoMa area, go eat at Crossroads Cafe or t
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Large-Scale Simulatanous Inference: Empirical Bayes (Efron, Stats 329)(www-stat.stanford.edu)
12 points by hamilton 17y ago|1 comments
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by hamilton 17y ago
igraph is also a must-have for network analysis in R. Great for data analysts familiar with the environment.
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Whereby Statistics Improves Your Dart Game(wired.com)
3 points by hamilton 17y ago|1 comments
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Climate Change Deniers Vs. The Consensus(informationisbeautiful.net)
4 points by hamilton 17y ago|0 comments
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by hamilton 17y ago
I think you're on to something regarding "significance." Over in my dept. we like to say that significance is a measure of sample size. The question, then, hinges on whether or not something has practical significance. Because we've buil
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by hamilton 17y ago
I beg to differ (not sure if you actually read the Efron talk I just posted). I get the thrust of the Less Wrong article, though I think that frankly his language and vitriol is direly misplaced. He's railing against some class of Frequen
69.
by hamilton 17y ago
This debate has been raging for 250 years. Brad Efron, one of the greatest living statisticians today and one of the few who can transcend the debate, has VERY interesting things to say about it. He believes that Empirical Bayes, or using
70.
by hamilton 17y ago
Lately I've been staring at the Codex Seriphinianus quite a bit. Worth finding a copy if you haven't seen it before. From a technical point of view, The Elements of Statistical Learning, by Tibshirani, Friedman, and Hastie. Far and away t
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by hamilton 17y ago
Everyone has given really great recommendations. I second caffeine's PROCESS. The way I learned most mathematics is from working through problems on a white board I bought. From there I got a great grasp of probability theory and linear