This is a short book with a lot in it. As the title says, its topic is the principles of data analysis. The emphasis is on why things are done rather than on exactly how to do them. If you already know something about the subject, then working through this book will probably deepen your understanding.
The book begins by identifying four general classes of data analysis problem, and uses elementary probability along with Bayes' theorem to explain exactly what each involves. The next two chapters use some simple distributions to illustrate these ideas. Further chapters discuss the Monte Carlo method briefly, least-squares fitting (in some detail), and the problem of determining a distribution function from data. The book ends with an interesting pair of chapters on entropy: one on the maximum entropy method, and one actually about thermodynamics.
The book is not aimed at absolute beginners. In general it's written for those who already know something about the subject, and want to understand more.
Prasenjit Saha, is at Queen Mary and Westfield College, University of London.