Finding Zero, by Amir Aczel. Dr. Aczel begins by describing the pleasures of growing up the son of a ship's captain, and particularly of being introduced to the mystery and joy of numbers by a ship's steward, Laci, who snuck him into a casino and later used playing cards to teach him about Arabic, Hindi and modern Arab numerals. This preschool experience was the first spark of his lifelong fascination with numerals and number theory, and at some point in his life, he apparently had the opportunity to travel the world hunting up the most ancient instances of numeral inscriptions he could find.
The Signal and the Noise, by Nate Silver. Subtitled "Why So Many Predictions Fail-- But Some Don't," it seems not entirely clear how it got in the Math section. It is classified as a book about "Forecasting," which I suppose is a subdiscipline of probability, about "Bayesian Statistical Decision Theory," so there you go, but also about "Knowledge, Theory of..." something that really should be found in the 010's with Black Swan. He opens with a discussion of the crash of 2008 and whether it was predictable or not, and gets very technical very fast, demonstrating how his brand of statistical and stochastic analysis could be applied to a variety of situations. Turns out one of the keystones of Bayesian statistical decision theory is that you have to acknowledge your biases-- your preferred outcome-- before you start, so that seems like a good idea.
Thinking in Numbers, by Daniel Tammet. I loved Born on a Blue Day, which told the story of how Tammet came to terms with all the things that made him neurologically exceptional. This book, like that one, showcases his warmth and his charming writing style, but doesn't seem as directed. The first essay is a series of musings on the number 9 and on set theory, occasioned by the fact that the set of Tammet children in his family of origin equalled 9. This seems like a good book to pick up and read in odd moments, maybe not straight through.
How Not to Be Wrong, by Jordan Ellenberg. Subtitled The Power of Mathematical Thinking, this book is about how math actually is something we can use to solve all kinds of real-life issues and think through whether we are even asking the right question. There are 18 different "episodes," or examples, one of which deals with Bayesian statistical analysis! Along the way, he's also going to help me understand what "expected value" is, which I've been worrying about ever since it came up on an ACT a while back. I like that he admits that it actually means "average" value. I am curious to see whether he is going to address the fact that the "average" value for almost anything is often the least useful piece of information you can obtain from a data set, as well as to find out about Biblical numerology and whether it is possible to game the lottery.
