who cringe when words such as "imply" and "infer" are confused react without a trace of embarrassment to even the most egregious of numerical solecisms. I remember once listening to someone at a party drone on about the difference between "continually" and "continuously." Later that evening we were watching the news, and the TV weathercaster announced that there was a 50 percent chance of rain for Saturday and a 50 percent chance for Sunday, and concluded that there was therefore a 100 percent chance of rain that weekend. The remark went right by the self-styled grammarian, and even after I explained the mistake to him, he wasn't nearly as indignant as he would have been had the weathercaster left a dangling participle. Chapters Examples and Principles. This chapter goes over how people's lack of clarity of very large numbers lead to misconceptions. He argues for scientific notation being a clearer way to work with larger numbers. The ability to put numbers large and small in the correct context is key to understanding them in an intelligent way. He gives examples in some jokes, Rubik's cube, nuclear weapons, travel at the speed of light, the number of three-scoop combinations at Baskin-Robbins, dice rolls, the chance of getting AIDS, and the chance of breathing the same molecule of breath as Julius Caesar. Probability and Coincidence. Underestimates of the frequency of coincidences is an example of innumeracy. People underestimate that an unlikely event is likely, given a large population sample. He gives examples in stock market newsletter scams, choosing a spouse, coincidence and the law, coin toss, and the hot-hand fallacy in sports. Pseudoscience. Here the author takes on how non-falsifiable statements play in with pseudoscience. For example Whatever God wills happens can not be proven false so is not part of science. He touches examples in Freud, Marx, parapsychology, dream prediction, astrology, UFOs, fraudulent medical treatments, conditional probability, blackjack, drug testing, and numerology. What is Innumeracy? Here the author critiques public math education; the need for estimation in the math curriculum; math and humor (Paulos suggests that mathematicians have a particular sense of humor); innumeracy and the tendency to personalize excessively versus a statistical analysis; selective filtering of data to draw incorrect conclusions; decisions and framing of questions; various misconceptions about math being cold, impersonal or constraining; and public safety risks. Statistics, Trade-Offs, and Society. This chapter addresses trade-offs in public policy,