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A cool article here on a group predicting the place/time when crime is going to happen. It looks like they are using a Poisson process. They liken it to predicting the after shocks of an earthquake. More details on the math behind the pre-cog software can be found here. I wonder what their prediction accuracy is? Thanks to Rafa for pointing the link out.
Many case studies I find interesting don’t appear in JASA Applications and Case Studies or other applied statistics journals for that matter. Some because the technical skill needed to satisfy reviewers is not sufficiently impressive, others because they lack mathematical rigor. But perhaps the main reason for this disconnect is that many interesting case studies are developed by people outside our field or outside academia.
In this blog we will try to introduce readers to some of these case studies. I’ll start it off by pointing readers to Nate Silver’s FiveThirtyEight blog. Mr. Silver (yes, Mr. not Prof. nor Dr.) is one of my favorite statisticians. He first became famous for PECOTA; a system that uses data and statistics to predict the performance of baseball players. In FiveThirtyEight he uses a rather sophisticated meta-analysis approach to predicting election outcomes.
For example, for the 2008 election he used data from the primaries to calibrate pollsters and then properly weighed these pollsters’ predictions to give a more precise estimate of election results. He predicted Obama would win 349 to 189 with a 6.1% difference in the popular vote. The actual result was 365 to 173 with a difference of 7.2%. His website included graphs that very clearly illustrated the uncertainty of his prediction. These were updated daily and I had a ton of fun visiting his blog at least once a day. I also learned quite a bit, used his data in class, and gained insights that I have used in my own projects.
About us:
We are three professors who are fired up about the new era where data is abundant and statisticians are scientists.
About this blog:
We’ll be posting ideas we find interesting, contributing to discussion of science/popular writing, and linking to articles that inspire us.
Why “Simply Statistics”:
We needed a title. Plus, we like the idea of using simple statistics to solve real, important problems. We aren’t fans of unnecessary complication - that just leads to lies, damn lies and something else.
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