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# Solution Manual for Linear Algebra A Modern Introduction 3rd Edition by David Poole

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### Solution Manual for Linear Algebra A Modern Introduction 3rd Edition by David Poole

#### Solution Manual for Linear Algebra A Modern Introduction 3rd Edition by David Poole

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• Chapter 1: Vectors
• 1.0: Introduction: The Racetrack Game
• 1.1: The Geometry and Algebra of Vectors (11)
• 1.2: Length and Angle: The Dot Product (7)
• 1.3: Lines and Planes (12)
• 1.4: Applications (7)
• 1: Chapter Review
• Chapter 2: Systems of Linear Equations
• 2.0: Introduction: Triviality
• 2.1: Introduction to Systems of Linear Equations (6)
• 2.2: Direct Methods for Solving Linear Systems (10)
• 2.3: Spanning Sets and Linear Independence (9)
• 2.4: Applications (11)
• 2.5: Iterative Methods for Solving Linear Systems (2)
• 2: Chapter Review
• Chapter 3: Matrices
• 3.0: Introduction:Matrices in Action
• 3.1: Matrix Operations (10)
• 3.2: Matrix Algebra (8)
• 3.3: The Inverse of a Matrix (9)
• 3.4: The LU Factorization (6)
• 3.5: Subspaces, Basis, Dimension, and Rank (7)
• 3.6: Introduction to Linear Transformations (9)
• 3.7: Applications (14)
• 3: Chapter Review
• Chapter 4: Eigenvalues and Eigenvectors
• 4.0: Introduction: A Dynamical System on Graphs
• 4.1: Introduction to Eigenvalues and Eigenvectors (7)
• 4.2: Determinants (9)
• 4.3: Eigenvalues and Eigenvectors of n n Matrices (6)
• 4.4: Similarity and Diagonalization (6)
• 4.5: Iterative Methods for Computing Eigenvalues (8)
• 4.6: Applications and the Perron-Frobenius Theorem (10)
• 4: Chapter Review
• Chapter 5: Orthogonality
• 5.0: Introduction: Shadows on a Wall
• 5.1: Orthogonality in ℝn (5)
• 5.2: Orthogonal Complements and Orthogonal Projections (8)
• 5.3: The Gram-Schmidt Process and the QR Factorization (7)
• 5.4: Orthogonal Diagonalization of Symmetric Matrices (5)
• 5.5: Applications (13)
• 5: Chapter Review
• Chapter 6: Vector Spaces
• 6.0: Introduction: Fibonacci in (Vector) Space
• 6.1: Vector Spaces and Subspaces (10)
• 6.2: Linear Independence, Basis, and Dimension (8)
• 6.3: Change of Basis (4)
• 6.4: Linear Transformations (6)
• 6.5: The Kernel and Range of a Linear Transformation (7)
• 6.6: The Matrix of a Linear Transformation (5)
• 6.7: Applications (6)
• 6: Chapter Review
• Chapter 7: Distance and Approximation
• 7.0: Introduction: Taxicab Geometry
• 7.1: Inner Product Spaces (4)
• 7.2: Norms and Distance Functions (6)
• 7.3: Least Squares Approximation (11)
• 7.4: The Singular Value Decomposition (6)
• 7.5: Applications (5)
• 7: Chapter Review
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