Statistical Treatment of Experimental Data

Recently I took a short course that included an introduction to statistics. The instructor glossed over much of that topic, saying it was too hard for our level and to let someone the next higher level up do the math. The next day I brought in this book, and told him that it was the book everyone in my (non-math) major at college learned statistics from. After we all learned statistics from this book, I never heard any of them complain that they didn't know or understand how to apply statistics. This book is not full of the theory of statistics. It tells the reader how to apply statistics, and gives easy to understand examples when introducing new ideas. The book covers probability, permutations, combinations, and the usual distributions (binomial, Poisson, Gaussian). A few concepts on goodness of fit and when to reject data are included, in addition to the propagation of errors, correlations, and least squares fitting. There is only a touch of differential equations in the book, being used to illustrate the origin of equations; otherwise the book is algebra-based. Problems are included at the end of the chapters, with answers listed in the back. The target audience for the book was originally undergraduate science and engineering majors. However, with the exception of a few of the homework problems, and the occasional example in the chapters, the book should be easily understood by anyone with a decent grasp of algebra. Nineteen years after buying it, I still use and learn from the book--not something I can say about many of the other textbooks I had to buy over the years.