Sunday data/statistics link roundup (4/28/2013)

  1. What it feels like to be bad at math. My personal experience like this culminated in some difficulties with Green's functions back in my early days at USU. I think almost everybody who does enough math eventually runs into a situation where they don't understand what is going on and it stresses them out.
  2. An article about companies that are using data to try to identify people for jobs (via Rafa).
  3. Google trends for predicting the market. I'm not sure that "predicting" is the right word here. I think a better word might be "explaining/associating". I also wonder if this could go off the rails.
  4. This article is ridiculously useful in terms of describing the ways that you can speed up R code. My favorite part of it is that it starts with the "why". Exactly. Premature optimization is the root of all evil.
  5. A discussion of data science at Tumblr. The author/speaker also has a great blog.
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  • Ben Orlin

    Hey Jeff, thanks for linking to my post on what it feels like to be bad at math. It's been nice hearing lots of accomplished math professionals respond with their own similar experiences.

    Simply Statistics looks like a great site, by the way - I've been having fun checking it out.

  • Thomas Lumley

    The optimisation page is good, although I was a bit put off to see in the introductory comments " For instance, x*x is faster than x^2 in R". It isn't, and it hasn't been for quite a long time. After that, fortunately, things improved a lot.

  • http://www.noamross.net/ Noam Ross

    Thanks for recommending my optimization post.