Review: Freakonimics by Steven D. Levitt and Stephen J. Dubner

I finished reading Freakonimics this weekend. I had heard many good things about it for the past few years, and I'm glad that I finally got around to reading it. It's not so much about economics as it is about drawing conclusions from large sets of data. That makes it sound boring, but the conclusions are in actuality really interesting.

But the conclusions would not be interesting without particularly interesting questions. A few questions of note:

• What caused the decline in crime in the 1990s?
• How can we identify teachers who try to cheat the testing systems?
• How much do parents really matter when predicting education outcomes?

What I actually found the most interesting were not necessarily Levitt's conclusions, but his methodology in reaching those conclusions. While there is certainly a good deal to be said about economic software, that software is useless if there is no clever way to create measurable sets of data and then sort it. I felt like there was just enough methodology to be interesting and make the problem clear without being bogged down with technical jargon.

I also found that as I read this book I wanted to tell Eric about every little bit that I read and what it could possibly mean in the greater picture. I think this would make a great book for a book club because it is non-fiction and has a lot of interesting discussion points.