Focusing on the computational aspects of statistics rather than the theoretical, Computational Statistics Handbook with MATLAB(r) uses a clown-to-earth approach that makes statistics accessible to a wide range of users. The authors integrate the use of MATLAB(r) throughout the book, allowing readers to see the actual implementation of algorithms. They also include step-by-step procedures so that the algorithms con be implemented using MATLAB(r) or any other suitable software. The book concentrates on the simulation/Monte Carlo point of view and contains algorithms for exploratory data analysis, modeling, Monte Carlo simulation, pattern recognition, bootstrap, classification, cross-validation methods, probability density estimation, random number generation, and other computational statistics methods. Emphasis on the practical aspects of statistics, details of the latest techniques, and real implementation experience make the Computational Statistics Handbook with MATLAB(r) more than just the first book to use MATLAB(r) to solve computational problems in statistics. It also forms an outstanding supplement to upper-level statistics course materials for those in the many disciplines that must deal with raw data.