These three books paired really well together. There was a little information overlap between the books, but each had a different and interesting focus.
As a librarian, I immediately felt a kinship with Nate Silver’s main premise: in a world of data, theory is more important, not less. It is a common argument that the internet and all of the data available to use at our fingertips replaces everything (including libraries). That the data speaks for itself. But more data can be a bad thing without theory. The examples throughout Silver’s book demonstrate that even experienced number crunchers run into limitations with what they can learn from their calculations and analysis and for people that don’t understand or ignore these limitations, the outcome can be disastrous. The first half of his book covers why predications go so wrong so often. The second discusses what can be done to make predictions better. Both parts of the book use topical examples to illustrate concepts, including online poker, politics, and earthquake prediction.
Michael Lewis’s book covers the lives of two psychologists, Daniel Kahneman and Amos Tversky, and their groundbreaking work in behavioral economics. They exposed the common biases we have when interpreting information, making decisions, and predicting outcomes. Many of these biases were referenced by Silver as a cause of predictions gone awry. The book is biographical. Both men survived Europe and the holocaust as children to start their careers in Israel during a time of great unrest and uncertainty.
Charles Wheelan took many of the concepts covered in intro to statistics and repackaged them in this insightful and often amusing book. He focuses on the underlying logic and intuition behind statistical analysis. Through real-world instances and by occasionally concocting a ridiculous example, Wheelan demonstrates where and how statistics can help us understand everyday problems.