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# Test Bank For Linear Algebra with Applications 2nd Edition| ©2017 by Holt

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Test Bank For Linear Algebra with Applications 2nd Edition| ©2017 by Jeffrey Holt,ISBN:9781319057701

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Test Bank For Linear Algebra with Applications 2nd Edition| ©2017 by Holt

Test Bank For Linear Algebra with Applications 2nd Edition| ©2017 by Jeffrey Holt,ISBN:9781319057701

Holt’s Linear Algebra with Applications, Second Edition, blends computational and conceptual topics throughout to prepare students for the rigors of conceptual thinking in an abstract setting. The early treatment of conceptual topics in the context of Euclidean space gives students more time, and a familiar setting, in which to absorb them. This organization also makes it possible to treat eigenvalues and eigenvectors earlier than in most texts. Abstract vector spaces are introduced later, once students have developed a solid conceptual foundation.

Concepts and topics are frequently accompanied by applications to provide context and motivation. Because many students learn by example, Linear Algebra with Applications provides a large number of representative examples, over and above those used to introduce topics. The text also has over 2500 exercises, covering computational and conceptual topics over a range of difficulty levels.
Preface
1. Systems of Linear Equations
1.1 Lines and Linear Equations
1.2 Linear Systems and Matrices
1.3 Applications of Linear Systems
1.4 Numerical Solutions
2. Euclidean Space
2.1 Vectors
2.2 Span
2.3 Linear Independence
3. Matrices
3.1 Linear Transformations
3.2 Matrix Algebra
3.3 Inverses
3.4 LU Factorization
3.5 Markov Chains
4. Subspaces
4.1 Introduction to Subspaces
4.2 Basis and Dimension
4.3 Row and Column Spaces
4.4 Change of Basis
5. Determinants
5.1 The Determinant Function
5.2 Properties of the Determinant
5.3 Applications of the Determinant
6. Eigenvalues and Eigenvectors
6.1 Eigenvalues and Eigenvectors
6.2 Diagonalization
6.3 Complex Eigenvalues and Eigenvectors
6.4 Systems of Differential Equations
6.5 Approximation Methods
7. Vector Spaces
7.1 Vector Spaces and Subspaces
7.2 Span and Linear Independence
7.3 Basis and Dimension
8. Orthogonality
8.1 Dot Products and Orthogonal Sets
8.2 Projection and the Gram-Schmidt Process
8.3 Diagonalizing Symmetric Matrices and QR Factorization
8.4 The Singular Value Decomposition
8.5 Least Squares Regression
9. Linear Transformations
9.1 Definition and Properties
9.2 Isomorphisms
9.3 The Matrix of a Linear Transformation
9.4 Similarity
10. Inner Product Spaces
10.1 Inner Products
10.2 The Gram-Schmidt Process Revisited
10.3 Applications of Inner Products