# Linear Algebra: A Modern Introduction International Edition 3rd edition

David Poole
Publisher: Cengage Learning

## eBook

Access is contingent on use of this textbook in the instructor's classroom.

Academic Term Homework Homework and eBook
Higher Education Single Term N/A N/A
Higher Education Multi-Term N/A N/A
High School N/A N/A

Online price per student per course or lab, bookstore price varies. Access cards can be packaged with most any textbook, please see your textbook rep or contact WebAssign

• 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

## Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

##### Question Availability Color Key
BLACK questions are available now
GRAY questions are under development

Group Quantity Questions
Chapter 1: Vectors
1.1 11 002 006 007 012 015 017 026 033 035 044 047
1.2 7 003 009 015 024 037 040 049
1.3 12 002 004 008 011 013 021 024 028 030 032 034 043
1.4 7 004 009 011 015 022 026 031
Chapter 2: Systems of Linear Equations
2.1 6 011 014 020 025 028 034
2.2 10 010 014 017 026 027 031 032 046 049 056
2.3 9 002 003 005 007 014 023 025 033 035
2.4 11 001 003 005 007 008 016 019 024 025 027 028
2.5 2 001 007
Chapter 3: Matrices
3.1 10 002 004 005 008 011 015 022 023 024 032
3.2 8 002 003 005 006 009 010 014 023
3.3 9 001 007 008 011 025 032 033 050 064
3.4 6 002 004 007 010 013 023
3.5 7 012 017 021 027 029 035 054
3.6 9 001 002 012 021 022 024 031 032 037
3.7 14 001 003 004 006 015 019 022 031 038 044 051 056 060 081
Chapter 4: Eigenvalues and Eigenvectors
4.1 7 003 010 014 017 024 027 033
4.2 9 003 008 017 022 036 046 049 058 062
4.3 6 002 003 015 017 027 035
4.4 6 002 004 006 013 016 024
4.5 8 002 004 005 010 017 030 034 047
4.6 10 003 008 012 029 033 034 044 048 059 077
Chapter 5: Orthogonality
5.1 5 004 005 009 011 017
5.2 8 002 004 007 009 012 013 017 020
5.3 7 002 003 005 007 009 015 017
5.4 5 001 003 007 017 023
5.5 13 002 006 009 015 023 031 036 043 063 068 075 078 089
Chapter 6: Vector Spaces
6.1 10 001 004 005 015 019 025 034 051 053 058
6.2 8 002 006 008 010 019 022 028 050
6.3 4 002 006 010 012
6.4 6 002 004 014 016 018 025
6.5 7 002 003 006 010 011 015 017
6.6 5 001 002 007 027 031
6.7 6 001 004 006 008 018 025
Chapter 7: Distance and Approximation
7.1 4 001 003 020 026
7.2 6 002 005 020 023 026 037
7.3 11 004 010 012 015 020 025 027 029 035 038 047
7.4 6 002 013 022 038 041 045
7.5 5 001 005 023 030 038
Total 300