Simply Statistics A statistics blog by Rafa Irizarry, Roger Peng, and Jeff Leek

Monday data/statistics link roundup (2/10/14)

I’m going to try Monday’s for the links. Let me know what you think.

  1. The Guardian is reading our blog. A week after Rafa posts that everyone should learn to code for career preparedness, the Guardian gets on the bandwagon.
  2. Nature Methods published a paper on a webtool for creating boxplots (via Simina B.). The nerdrage rivaled the quilt plot. I’m not opposed to papers like this being published, in fact it is an important part of making sure we don’t miss out on the good software when it comes. There are two important things to keep in mind though: (a) Nature Methods grades on a heavy “innovative” curve which makes it pretty hard to publish papers there, so publishing papers like this could cause frustration among people who would submit there and (b) if you use the boxplots from using this tool you must cite the relevant software that generated the boxplot.
  3. This story about Databall (via Rafa.) is great, I love the way that it talks about statisticians as the leaders on a new data type. I also enjoyed reading the paper the story is about. One interesting thing about that paper and many of the papers at the Sloan Sports Conference is that the data are proprietary (via Chris V.) so the code/data/methods are actually not available for most papers (including this one). In the short term this isn’t a big deal, the papers are fun to read. In the long term, it will dramatically slow progress. It is almost always a bad long term strategy to make data private if the goal is to maximize value.
  4. The P-value curve for fixing publication bias (via Rafa). I think it is an interesting idea, very similar to our approach for the science-wise false discovery rate. People who liked our paper will like the P-value curve paper. People who hated our paper for the uniformity under the null assumption will hate that paper for the same reason (via David S.)
  5. Hopkins discovers bones are the best (via Michael R.).
  6. Awesome scientific diagrams in tex. Some of these are ridiculous.
  7. Mary Carillo goes crazy on backyard badminton. This is awesome. If you love the Olympics and the internet, you will love this (via Hilary P.)
  8. B’more Biostats has been on a tear lately. I’ve been reading [I’m going to try Monday’s for the links. Let me know what you think.

  9. The Guardian is reading our blog. A week after Rafa posts that everyone should learn to code for career preparedness, the Guardian gets on the bandwagon.
  10. Nature Methods published a paper on a webtool for creating boxplots (via Simina B.). The nerdrage rivaled the quilt plot. I’m not opposed to papers like this being published, in fact it is an important part of making sure we don’t miss out on the good software when it comes. There are two important things to keep in mind though: (a) Nature Methods grades on a heavy “innovative” curve which makes it pretty hard to publish papers there, so publishing papers like this could cause frustration among people who would submit there and (b) if you use the boxplots from using this tool you must cite the relevant software that generated the boxplot.
  11. This story about Databall (via Rafa.) is great, I love the way that it talks about statisticians as the leaders on a new data type. I also enjoyed reading the paper the story is about. One interesting thing about that paper and many of the papers at the Sloan Sports Conference is that the data are proprietary (via Chris V.) so the code/data/methods are actually not available for most papers (including this one). In the short term this isn’t a big deal, the papers are fun to read. In the long term, it will dramatically slow progress. It is almost always a bad long term strategy to make data private if the goal is to maximize value.
  12. The P-value curve for fixing publication bias (via Rafa). I think it is an interesting idea, very similar to our approach for the science-wise false discovery rate. People who liked our paper will like the P-value curve paper. People who hated our paper for the uniformity under the null assumption will hate that paper for the same reason (via David S.)
  13. Hopkins discovers bones are the best (via Michael R.).
  14. Awesome scientific diagrams in tex. Some of these are ridiculous.
  15. Mary Carillo goes crazy on backyard badminton. This is awesome. If you love the Olympics and the internet, you will love this (via Hilary P.)
  16. B’more Biostats has been on a tear lately. I’ve been reading](http://lcolladotor.github.io/2014/02/05/DropboxAndGoogleDocsFromR/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+FellgernonBit+%28Fellgernon+Bit%29) on uploading files to Dropbox/Google drive from R, Mandy’s post explaining quantitative MRI, Yenny’s post on data sciences, John’s post on graduate school open houses, and Alyssa’s post on vectorization. If you like Simply Stats you should be following them on Twitter here.