One of my favorite statistics books that just makes you want to learn data analysis is Freakonomics : A Rogue Economist Explores the Hidden Side of Everything by Steven Levitt - an economist from the University of Chicago who was recently awarded the John Bates Clark Medal, and Stephen Dubner - an author and writer for the NYT and The New Yorker. Together they created a rare product: a data analysis books to take to bed!
The book describes several somewhat-wild studies in an attempt to answer questions that your kids might have asked you: "Why do drug dealers still live with their moms?" or "What do schoolteachers and Sumo wrestlers have in common?". The beauty of these studies is the creativity in the question of interest, sometimes the data collection or experimental design, structuring the analysis, and the interpretation of the results. It shows how careful modeling can lead to very interesting (if somewhat untraditional) insights.
It is an easy, fun read. And for those who know something about regression models, that is the main tool used. Recommending this to students at the start of the data analysis class usually brings a few back with starry eyes.
Turns out that the book is actually used in a variety of university courses and there is even a free study guide!
And of course, if you get totally hooked, there is a freakonomics blog.