See also books on the S programming language and on the SAS programming language.
Publisher’s information  Comments 

Applied Regression Analysis and Other Multivariable Methods
3rd edition by David G. Kleinbaum, Lawrence L. Kupper, Keith E. Muller, and Azhar Nizam 1998 Duxbury Press ISBN 0534209106 
This is the text chosen for Boston University's CAS MA 684, Multivariate Analysis, course, which I took in the spring semester of 2006. The course was an applied statistics course for statistics majors and graduate students in other fields who need to perform statistical analysis of their data. The book provides a nice mix of theory and application. The chapters are short and concentrate on what main idea each. There is a lot of SAS output included in the book, but strangely the book doesn't include the SAS programs used to generate the output. The book’s chapters are:

The Elements of Statistical Learning
by Trevor Hastie, Robert Tibshirani, and Jerome Friedman October 2001 Springer ISBN 0387952845 
This is a beautifully produced book with 200 full color figures. It will take me years to master all the methods presented. The book’s chapters are:

A First Course in Probability
6th edition by Sheldon Ross 2002 Pearson Prentice Hall ISBN 0130338516 
This is an excellent book on probability. Ross takes some interesting tangents to solve unusual problems. The chapters are:

Introduction to Mathematical Statistics
6th edition by Robert V. Hogg, Joseph W. McKean, and Allen T. Craig 2005 Pearson Prentice Hall ISBN 0130085073 
This book was the required text for Boston University's MET MA 582, Mathematical Statistics, course. This is a difficult book with enough material for three semesters. The material is wellwritten and rewards hard work. Most unusual, the book contains some S code that can be run using R or SPLUS. The chapters are:

Introduction to Probability
2nd edition by Charles M. Grinstead and J. Laurie Snell 1997 American Mathematical Society ISBN 0821807498 
A free PDF version of this book is now available. The chapters are:

John E. Freund’s Mathematical Statistics with Applications
7th edition by Irwin Miller and Maryless Miller 2004 Pearson Prentice Hall ISBN 0131427067 
When I was taking Mathematical Statistics at Boston University, sometimes the assigned text (Introduction to Mathematical Statistics by Hogg, McKean, and Craig) was too difficult. I purchased this book as a supplementary text and discovered that this book had probably provided the source material for the professor’s lectures. This book covers the same material as Hogg, McKean, and Craig, but on a less rigorous level. There is less emphasis on theory and more emphasis on application. The chapters are:

Mathematical Statistics and Data Analysis
2nd Edition by John A. Rice September 1994 Duxbury Press ISBN 0534209343 
This statistics textbook is recommended for juniors, seniors, or graduate students who have had a year of introductory statistics, three semesters of calculus (through multivariate calculus), and a semester of linear algebra. I use this book regularly, and I recommend it highly. 
Mathematical Statistics with Mathematica
by Colin Rose and Murray D. Smith March 2002 Springer ISBN 0387952349 
The book includes a CD with mathStatica and a trial version of Mathematica 4. 
Multivariate Statistical Methods
3rd Edition by Donald F. Morrison November 1990 McGrawHill, Inc. ISBN 0070431876 
Morrison provides an exceptionally clear presentation of multivariate statistics, including discriminant functions, covariance matrices, principal component analysis, and factor analysis. Linear algebra and matrices are used extensively throughout the book. This book is sadly out of print; I obtained my copy from an online used book dealer. 
Principal Component Analysis
2nd edition by I. T. Jolliffe July 2002 Springer ISBN 0387954422 
This book provides exhaustive coverage of principal component analysis, a popular method of reducing the dimensionality of multivariate data. 
Principles of Data Mining
by David Hand, Heikki Mannila, and Padhraic Smyth 2001 The MIT Press ISBN 026208290X 
This is a very readable introduction to methods used for data mining. The book’s chapters are:

Stat Labs: Mathematical Statistics Through Applications
by Deborah Nolan and Terry Speed 2000 Springer ISBN 0387989749 
This book provides a series of indepth case studies that present realworld data sets for analysis by the student. The book’s web site includes special intructions for users of R and SPLUS. 
Statistics for Experimenters
by George E. P. Box, William G. Hunter, and J. Stuart Hunter October 1978 John Wiley & Sons ISBN 0471093157 
A classic, this book is a highly readable introduction to experimental design. The 2nd edition was published in 2005. 
Statistical Methods in Bioinformatics
by Warren J. Ewens and Gregory R. Grant July 2001 Springer ISBN 0387952292 
This book presents probability and statistics for sequence analysis. A second edition has since been published. 