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  1. Pinned Tweet

    'Errors using inadequate data are much less than those using no data at all.' -- Charles Babbage

  2. The Wilcoxon Rank Sum Test can have greater asymptotic relative efficiency than the t-test for heavy-tailed distributions.

  3. No amount of data can persuade you of something you assign zero prior probability to. -- Cromwell's rule

  4. Linear regression is much more than curve-fitting.

  5. The First Release of PyMC3

  6. Saw a comment in code "Do something with this information." Ah, that's the hard part. '

  7. FWHM = full width at half maximum. Distance between points on either side of the mode where a function takes half its maximum value.

  8. You can learn things from a dozen human subjects you couldn't learn from a million mice. Data relevance beats data size.

  9. Bayesian and nonlinear

  10. R. A. Fisher was the first to use the term 'Bayesian,' and he didn't mean it as a compliment.

  11. Three reasons a method might perform worse with more data, and how to fix them.

  12. New post: Native Hadoop file system (HDFS) connectivity in Python

  13. 'A statistical analysis, properly conducted, is a delicate dissection of uncertainties, a surgery of suppositions.' -- M. J. Moroney

  14. Beer, wine, and statistics

  15. 'Everyone thinks that the data in other people’s subjects are in better shape.' -- John Tukey

  16. How to test a random number generator

  17. For network analysis, check out .

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