Schaum's Outline of Linear Algebra

Helps readers use examples to solve problems; brush up before tests; find answers; study effectively; and get the big picture without poring over lengthy textbooks. This guide provides explanations of eigenvalues, eigenvectors, linear transformations, linear equations, vectors, and matrices.

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Master linear algebra with "Schaum's" - the high-performance study guide. It will help you cut study time, hone problem-solving skills, and achieve your personal best on exams and projects! Students love "Schaum's Outlines" because they produce results. Each year, hundreds of thousands of students improve their test scores and final grades with these indispensable study guides. Get the edge on your classmates. Use "Schaum's"! If you don't have a lot of time but want to excel in class, this book helps you: use detailed examples to solve problems; brush up before tests; find answers fast; study quickly and more effectively; and, get the big picture without poring over lengthy textbooks."Schaum's Outlines" give you the information your teachers expect you to know in a handy and succinct format - without overwhelming you with unnecessary jargon. You get a complete overview of the subject. Plus, you get plenty of practice exercises to test your skill. Compatible with any classroom text, "Schaum's" let you study at your own pace and remind you of all the important facts you need to remember - fast!
And "Schaum's" are so complete, they're perfect for preparing for graduate or professional exams.Inside, you will find: a bridge between computational calculus and formal mathematics; clear explanations of eigenvalues, eigenvectors, linear transformations, linear equations, vectors, and matrices; solved problems that relate to the field you are studying; and, easy-to-understand information, perfect for pre-test review. If you want top grades and a thorough understanding of linear algebra, this powerful study tool is the best tutor you can have! The chapters include: Vectors in Rn and Cn; Matrix Algebra; Linear Equations; Vector Spaces; Linear Mappings; Linear Mapings and Matrices; Inner Product Spaces, Orthogonality; Determinants; Diagonalization: Eigenvalues and Eigenvectors; Canonical Forms; Linear Functionals and the Dual Space; Bilinear, Quadratic, and Hermitian Forms; Linear Operators on Inner Product Spaces; and, Polynomials.