Sunday Data/Statistics Link Roundup (11/4/12)

1. Brian Caffo headlines the WaPo article about massive online open courses. He is the driving force behind our department’s involvement in offering these massive courses. I think this sums it up: `“I can’t use another word than unbelievable,” Caffo said. Then he found some more: “Crazy . . . surreal . . . heartwarming.”’
2. A really interesting discussion of why “A Bet is a Tax on B.S.”. It nicely describes why intelligent betters must be disinterested in the outcome, otherwise they will end up losing money. The Nate Silver controversy just doesn’t seem to be going away, good news for his readership numbers, I bet. (via Rafa)
3. An interesting article on how scientists are not claiming global warming is the sole cause of the extreme weather events we are seeing, but that it does contribute to them being more extreme. The key quote: “We can’t say that steroids caused any one home run by Barry Bonds, but steroids sure helped him hit more and hit them farther. Now we have weather on steroids.” —Eric Pooley. (via Roger)
4. The NIGMS is looking for a Biomedical technology, Bioinformatics, and Computational Biology Director. I hope that it is someone who understands statistics! (via Karl B.)
5. Here is another article that appears to misunderstand statistical prediction.  This one is about the Italian scientists who were jailed for failing to predict an earthquake. No joke. 
6. We talk a lot about how much the data revolution will change industries from social media to healthcare. But here is an important reality check. Patients are not showing an interest in accessing their health care data. I wonder if part of the reason is that we haven’t come up with the right ways to explain, understand, and utilize what is inherently stochastic and uncertain information. 
7. The BMJ is now going to require all data from clinical trials published in their journal to be public.  This is a brilliant, forward thinking move. I hope other journals will follow suit. (via Karen B.R.)
8. An interesting article about the impact of retractions on citation rates, suggesting that papers in fields close to those of the retracted paper may show negative impact on their citation rates. I haven’t looked it over carefully, but how they control for confounding seems incredibly important in this case. (via Alex N.).