finelybook
Linear Algebra and Its Applications
by 作者: 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
