Matrix Algebra Useful for Statistics (Wiley Series in Probability and Statistics) by Shayle R. Searle (Author), André I. Khuri (Co-author). Updated to the 2nd Edition, this guide explores matrix algebra essential for statistical analysis. It features applied illustrations, numerical examples, and exercises. New coverage includes vector spaces, linear transformations, and computational aspects of matrices. The book discusses balanced linear models using direct products of matrices and covers multiresponse linear models. SAS, MATLAB, and R are extensively used throughout to perform matrix computations. Originally published on May 1, 2017, this edition continues to be a self-contained resource presented in an explanatory style.