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## About The linear algebra a modern introduction 4th edition by david poole pdf Book

Linear algebra a modern introduction 4th edition David Poole pdf innovative book prepares students to make the transition from the computational aspects of the course to the theoretical by emphasizing vectors and geometric intuition from the start. Designed for a one- or two-semester introductory course and written in simple, “mathematical English” linear algebra david poole 4th edition pdf presents interesting examples before abstraction. This immediately follows up theoretical discussion with further examples and a variety of applications drawn from a number of disciplines, which reinforces the practical utility of the math, and helps students from a variety of backgrounds and learning styles stay connected to the concepts they are learning.linear algebra a modern introduction by david poole 4th edition pdf helps students succeed in this course by learning vectors and vector geometry first in order to visualize and understand the meaning of the calculations that they will encounter and develop mathematical maturity for thinking abstractly.

## Table of Contents for poole linear algebra a modern introduction 4th edition pdf

Chapter 1

Vectors

Chapter 2

Systems Of Linear Equations

2.1 Introduction to Systems of Linear Equations Exercises p.63

2.2 Direct Methods for Solving Linear Systems Exercises p.79

2.3 Spanning Sets and Linear Independence Exercises p.97

2.4 Applications Exercises p.113

2.5 Iterative Methods for Solving Linear Systems Exercises p.132

Chapter Review p.134

Chapter 3

Matrices

3.1 Matrix Operations Exercises p.152

3.2 Matrix Algebra Exercises p.161

3.3 The Inverse of a Matrix Exercises p.178

3.4 The LU Factorization Exercises p.189

3.5 Subspaces, Basis, Dimension, and Rank Exercises p.209

3.6 Introduction to Linear Transformations Exercises p.223

3.7 Applications Exercises p.245

Chapter Review p.252

Chapter 4

Eigenvalues And Eigenvectors

4.1 Introduction to Eigenvalues and Eigenvectors Exercises p.260

4.2 Determinants Exercises p.281

4.3 Eigenvalues and Eigenvectors of n X n Matrices Exercises p.298

4.4 Similarity and Diagonalization Exercises p.309

4.5 Iterative Methods for Computing Eigenvalues Exercises p.323

4.6 Applications and the Perron-Frobenius Theorem Exercises p.359

Chapter Review p.365

Chapter 5

Orthogonality

5.1 Orthogonality in R^n Exercises p.376

5.2 Orthogonal Complements and Orthogonal Projections Exercises p.387

5.3 The Gram-Schmidt Process and the QR Factorization Exercises p.394

5.4 Orthogonal Diagonalization of Symmetric Matrices Exercises p.407

5.5 Applications Exercises p.423

Chapter Review p.425

Chapter 6

Vector Spaces

6.1 Vector Spaces and Subspaces Exercises p.441

6.2 Linear Independence, Basis, and Dimension Exercises p.456

6.3 Change of Basis Exercises p.471

6.4 Linear Transformations Exercises p.480

6.5 The Kernel and Range of a Linear Transformation Exercises p.495

6.6 The Matrix of a Linear Transformation Exercises p.512

6.7 Applications Exercises p.525

Chapter Review p.527

Chapter 7

Distance And Approximation

7.1 Inner Product Spaces Exercises p.540

7.2 Norms and Distance Functions Exercises p.566

7.3 Least Squares Approximation Exercises p.586

7.4 The Singular Value Decomposition Exercises p.609

7.5 Applications Exercises