While anyone who has dealt with statistics in a professional capacity is probably familiar with the contents already, it is still a handy little reference. And for anyone in an introductory course of study or who is simply concerned enough to wonder about the truth of what they read, this is absolutely invaluable.
It is not a long book, and some of the examples are dated (physicians recommending brands of tobacco, for instance), but the meat of the book is both accurate and extremely readable. It covers the ways that statistics can be made to show pretty much anything, both through deliberate manipulation and through simple sloppiness. The main chapters cover issues such as inadequate and biased samples, how to provide subtly and not-so-subtly misleading (though technically accurate) visual charts and representations, how to manipulate perception by eliminating inconvenient precision and adding spurious precision, how to manipulate perception by supplying numbers without context or by simply leaving inconvenient facts out, and how to confuse people thoroughly about correlation vs. cause-and-effect. The final chapter provides a nice summary: the questions you absolutely must ask about any figure you are presented with, in order to judge its worth.
As the author himself says, it may read something like a graduate text on dishonesty, but one can assume that people who deliberately wish to mislead have figured out how already; this is to educate the honest person who wishes to be alert. It is frequently used as a text in undergraduate statistics courses, for good reason.