Linear Algebra and Its Applications

by:David C Lay , Steven R Lay , Judi J McDonald

Publisher Finelybook 出版社：Pearson; 6th ed. edition (3 Feb. 2020)

Language 语言：English

pages 页数：672 pages

ISBN-10 书号：0135851254

ISBN-13 书号：9780135851258**Book Description**

This print textbook is available for students to rent for their classes. The Pearson print rental program provides students with affordable access to learning materials, so they come to class ready to succeed.

For courses in Linear Algebra.

Fosters the concepts and skills students will use in future careers

Linear Algebra and Its Applications offers a modern elementary introduction with broad, relevant applications. With traditional texts, the early stages of the course are relatively easy as material is presented in a familiar, concrete setting; but students often hit a wall when abstract concepts are introduced. Certain concepts fundamental to the study of linear algebra (such as linear independence, vector space, and linear transformations) require time to learn-and students’ understanding of them is vital.

Lay, Lay, and McDonald make these concepts more accessible by introducing them early in a familiar, concrete Rn setting, developing them gradually, and returning to them throughout the text so that students can grasp them when they are discussed in the abstract. Throughout, the 6th Edition updates exercises, adds new applications, takes advantage of improved technology, and offers more support for conceptual learning.

Also available with MyLab Math

By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student.

0135851254 / 9780135851258 LINEAR ALGEBRA AND ITS APPLICATIONS [RENTAL EDITION], 6/e

Table of contents:

Linear Algebra and Its Applications 6th Edition [David C. Lay]

Applications Index

Title Page

Copyright

Dedication

Contents

Pref ace

A Note to Students

Chapter 1 Linear Equations in Linear Algebra

Chapter 2 Matrix Algebra

Chapter 3 Determinants

Chapter 4 Vector Spaces

Chapter 5 Eigenvalues and Eigenvectors

Chapter 6 Orthogonality and Least Squares

Chapter 7 Symmetric Matrices and Quadratic Forms

Chapter 8 The Geometry of Vector Spaces

Chapter 9 blanchard

Chapter 10 Finite-State Markov Chains

Appendix 1 Proof of Theorem 1

Appendix 2 Probability

Chapter 10:Answers to Exercises

Appendix A Uniqueness of the Reduced Echelon Form

Appendix B Complex Numbers

Credits

Glossary

Answers to Odd-Numbered Exercises

Index

Advice on Reading Linear Algebra

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