Most popular infographics

Thanks to Karl Broman via Andrew Gelman.

The Killer App for Peer Review

A little while ago, over at Genomes Unzipped, Joe Pickrell asked, “Why publish science in peer reviewed journals?” He points out the flaws with the current peer review system and suggests how we can do better. What he suggests is missing is the killer app for peer review. 

Well, PLoS has now developed an API, where you can easily access tons of data on the papers published in those journals including downloads, citations, number of social bookmarks, and mentions in major science blogs. Along with Mendeley a free reference manager, they have launched an competition to build cool apps with their free data. 

Seems like with the right statistical analysis/cool features a recommender system for say, PLoS One could have most of the features suggested by Joe in his article. One idea would be an RSS-feed based on an idea like the Pandora music sharing service. You input a couple of papers you like from the journal, then it creates an RSS feed with papers similar to that paper. 

StatistiX

I think our field would attract more students if we changed the name to something ending with X or K. I’ve joked about this for years, but someone has actually done it (kind of):

http://www.bitlifesciences.com/AnalytiX2012/

Small ball is a bad strategy

Bill James pointed this out a long time ago. If you don’t know Bill James, you should look him up. I consider him to be one of the most influential statisticians of all times. This post relates to one of his first conjectures: sacrificing outs for runs, referred to as small ball, is a bad strategy. 

ESPN’s Gamecast, a webtool that gives you pitch-by-pitch updates of baseball games, also gives you a pitch-by-pitch “probability” of wining. Gamecast confirms the conjecure with data. How do they calculate this “probability”? I am pretty sure it is based only on historical data. No modeling. For example, if the away team is up 4-2 in the bottom of the 7th with no outs and runners on 1st and 2nd, they look at all the instances exactly like this one that have ever happened in the digitally recorded history of baseball and report the proportion of times the home team wins. Well in this situation this proportion is 45%. If the next batter successfully bunts, moving the runners over, this proportion drops to 41%.  Furthermore, if after the successful bunt, the run from third scores on a sacrifice fly, the proportion drops again from 41%  to 39%. The extra out hurts you more than the extra run helps you. That was Bill James’ intuition: you only have three outs so the last thing you want to do is give 33% away. 

MacArthur Fellow Shwetak Patel

The new MacArthur Fellows list is out and, as usual, they are an interesting bunch. One person that I thought was worth pointing out is Shwetak Patel. I had the privilege of meeting Shwetak at a National Research Council meeting on sustainability and computer science. Basically, he’s working on devices that you can install in your home to monitor your resource usage. He’s already spun-off a startup company to make/sell some of these devices. 

In the writeup for the award, they mention

When coupled with a machine learning algorithm that analyzes patterns of activity and the signature noise produced by each appliance, the sensors enable users to measure and disaggregate their energy and water consumption and to detect inefficiencies more effectively.

Now that’s statistics at work!