A thoroughly updated guide to matrix algebra and its uses in statistical analysis and features SAS(R), MATLAB(R), and r throughout this second edition addresses matrix algebra that is useful in the statistical analysis of data as well as within statistics as a whole. The material is presented in an explanatory style rather than a formal theorem-proof format and is self-contained. Featuring numerous applied illustrations, numerical examples, and exercises, the book has been updated to include the use of SAS, MATLAB, and r for the execution of matrix computations. In addition, andre i. Khuri, who has extensive research and teaching experience in the field, joins this new edition as co-author. The second edition also: * contains new coverage on vector spaces and linear transformations and discusses computational aspects of matrices * covers the analysis of balanced linear models using direct products of matrices.