This comprehensive text covers both applied and theoretical branches of matrix algebra in the statistical sciences. It begins by dealing with the basic structure of vectors and vector spaces and then emphasizes the diverse properties of matrices and their associated linear transformations — and how these, in turn, depend upon results derived from linear vector spaces.1983 edition. Republication of the New York, 1983 edition.
Matrices and Linear Algebra by Hans Schneider, George Phillip Barker Basic textbook covers theory of matrices and its applications to systems of linear equations and related topics such as determinants, eigenvalues and differential equations. Includes numerous exercises.
Statistical Inference by Vijay K. Rohatgi This treatment of probability and statistics examines discrete and continuous models, functions of random variables and random vectors, large-sample theory, more. Hundreds of problems (some with solutions). 1984 edition. Includes 144 figures and 35 tables.
Basic Algebra I: Second Edition by Nathan Jacobson A classic text and standard reference for a generation, this volume covers all undergraduate algebra topics, including groups, rings, modules, Galois theory, polynomials, linear algebra, and associative algebra. 1985 edition.
