Linear algebra and its applications / Gilbert Strang.

David Poole’s innovative LINEAR ALGEBRA: A MODERN INTRODUCTION, 4e emphasizes a vectors approach and better prepares students to make the transition from computational to theoretical mathematics. Balancing theory and applications, the book is written in a conversational style and combines a traditional presentation with a focus on student-centered learning. Theoretical, computational, and applied topics are presented in a flexible yet integrated way. Stressing geometric understanding before computational techniques, vectors and vector geometry are introduced early to help students visualize concepts and develop mathematical maturity for abstract thinking. Additionally, the book includes ample applications drawn from a variety of disciplines, which reinforce the fact that linear algebra is a valuable tool for modeling real-life problems.

Previous ed.: San Diego, CA : Harcourt College Publishers, c1988.

“Technology Bytes”, an extensive online appendix that shows Maple, Mathematica, and MATLAB instructions key for working out examples and exercises from the text in a computer algebra system.
Explorations provide deeper discovery-based guides on key concepts, designed for individual or group work.
Ample applied problems from a wide variety of disciplines, including mathematics, physics, engineering, biology, chemistry, computer science, economics, geography, psychology, and sociology.
Context-sensitive margin notes for extra help and cross-references.
Vignettes showcase modern applications of linear algebra.
Biographical sketches highlight many of the mathematicians who contributed to the development of linear algebra.
Writing Projects offer students opportunities to research and write about linear algebra. Projects are designed for individual or group work.
Chapter 8: Codes is an online chapter combining all material on codes previously interspersed throughout the text.
More than 100 new or revised exercises.

Table of Contents 1. Vectors.

2. Systems of linear equations.

3. Matrices.

4. Eigenvalues and eigenvectors.

5. Orthogonality.

6. Vector spaces.

7. Distance and approximation.

Appendix B: Mathematical Induction.

Appendix C: Complex Numbers.

Appendix D: Polynomials.