Post date: Apr 7, 2014 6:08:29 PM
A nice summary of some of the issues in 'theory-free' correlational analysis and the potential for big data to make big mistakes even bigger. In Big Data: Are we making a big mistake? (3/28/14) Harford lays out many of the issues we have been discussing in class, but in the context of very large data sets.
"The big data craze threatens to be The Literary Digest all over again. Because found data sets are so messy, it can be hard to figure out what biases lurk inside them – and because they are so large, some analysts seem to have decided the sampling problem isn’t worth worrying about. It is."