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Linear Algebra and Its Applications by David C. Lay 2011, Hardcover Book

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book has staining on top of book see photos for condition
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eBay item number:186229891574

Item specifics

Condition
Acceptable
A book with obvious wear. May have some damage to the book cover but the book is still completely intact. The binding may be slightly damaged around the edges but it is still completely intact. May have some underlining and highlighting of text and some writing in the margins, but there are no missing pages or anything else that would compromise the readability or legibility of the text. See the seller’s listing for full details and description of any imperfections. See all condition definitionsopens in a new window or tab
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“book has staining on top of book see photos for condition”
Subject
Algebra / Linear, Algebra / General
ISBN
9780321385178
Subject Area
Mathematics
Publication Name
Linear Algebra and Its Applications
Publisher
Addison Wesley
Item Length
10.3 in
Publication Year
2011
Type
Textbook
Format
CD-ROM / Trade Paperback
Language
English
Item Height
0.9 in
Author
David C. Lay
Item Weight
40.2 Oz
Item Width
8.3 in
Number of Pages
576 Pages

About this product

Product Information

Linear algebra is relatively easy for students during the early stages of the course, when the material is presented in a familiar, concrete setting. But when abstract concepts are introduced, students often hit a brick wall. Instructors seem to agree that certain concepts (such as linear independence, spanning, subspace, vector space, and linear transformations), are not easily understood, and require time to assimilate. Since they are fundamental to the study of linear algebra, students' understanding of these concepts is vital to their mastery of the subject. David Lay introduces these concepts early in a familiar, concrete "Rn " setting, develops them gradually, and returns to them again and again throughout the text so that when discussed in the abstract, these concepts are more accessible. Note: This is the standalone book, if you want the book/access card order the ISBN below. 0321399145 / 9780321399144 Linear Algebra plus MyMathLab Getting Started Kit for Linear Algebra and Its Applications Package consists of: 0321385179 / 9780321385178 Linear Algebra and Its Applications 0321431308 / 9780321431301 MyMathLab/MyStatLab -- Glue-in Access Card 0321654064 / 9780321654069 MyMathLab Inside Star Sticker "

Product Identifiers

Publisher
Addison Wesley
ISBN-10
0321385179
ISBN-13
9780321385178
eBay Product ID (ePID)
99619897

Product Key Features

Number of Pages
576 Pages
Language
English
Publication Name
Linear Algebra and Its Applications
Publication Year
2011
Subject
Algebra / Linear, Algebra / General
Type
Textbook
Subject Area
Mathematics
Author
David C. Lay
Format
CD-ROM / Trade Paperback

Dimensions

Item Height
0.9 in
Item Weight
40.2 Oz
Item Length
10.3 in
Item Width
8.3 in

Additional Product Features

Edition Number
4
Dewey Edition
23
Target Audience
College Audience
Dewey Decimal
512.5
Table of Content
1. Linear Equations in Linear Algebra Introductory Example: Linear Models in Economics and Engineering 1.1 Systems of Linear Equations 1.2 Row Reduction and Echelon Forms 1.3 Vector Equations 1.4 The Matrix Equation Ax = b 1.5 Solution Sets of Linear Systems 1.6 Applications of Linear Systems 1.7 Linear Independence 1.8 Introduction to Linear Transformations 1.9 The Matrix of a Linear Transformation 1.10 Linear Models in Business, Science, and Engineering Supplementary Exercises 2. Matrix Algebra Introductory Example: Computer Models in Aircraft Design 2.1 Matrix Operations 2.2 The Inverse of a Matrix 2.3 Characterizations of Invertible Matrices 2.4 Partitioned Matrices 2.5 Matrix Factorizations 2.6 The Leontief Input Output Model 2.7 Applications to Computer Graphics 2.8 Subspaces of Rn 2.9 Dimension and Rank Supplementary Exercises 3. Determinants Introductory Example: Random Paths and Distortion 3.1 Introduction to Determinants 3.2 Properties of Determinants 3.3 Cramer''s Rule, Volume, and Linear Transformations Supplementary Exercises 4. Vector Spaces Introductory Example: Space Flight and Control Systems 4.1 Vector Spaces and Subspaces 4.2 Null Spaces, Column Spaces, and Linear Transformations 4.3 Linearly Independent Sets; Bases 4.4 Coordinate Systems 4.5 The Dimension of a Vector Space 4.6 Rank 4.7 Change of Basis 4.8 Applications to Difference Equations 4.9 Applications to Markov Chains Supplementary Exercises 5. Eigenvalues and Eigenvectors Introductory Example: Dynamical Systems and Spotted Owls 5.1 Eigenvectors and Eigenvalues 5.2 The Characteristic Equation 5.3 Diagonalization 5.4 Eigenvectors and Linear Transformations 5.5 Complex Eigenvalues 5.6 Discrete Dynamical Systems 5.7 Applications to Differential Equations 5.8 Iterative Estimates for Eigenvalues Supplementary Exercises 6. Orthogonality and Least Squares Introductory Example: Readjusting the North American Datum 6.1 Inner Product, Length, and Orthogonality 6.2 Orthogonal Sets 6.3 Orthogonal Projections 6.4 The Gram Schmidt Process 6.5 Least-Squares Problems 6.6 Applications to Linear Models 6.7 Inner Product Spaces 6.8 Applications of Inner Product Spaces Supplementary Exercises 7. Symmetric Matrices and Quadratic Forms Introductory Example: Multichannel Image Processing 7.1 Diagonalization of Symmetric Matrices 7.2 Quadratic Forms 7.3 Constrained Optimization 7.4 The Singular Value Decomposition 7.5 Applications to Image Processing and Statistics Supplementary Exercises 8. The Geometry of Vector Spaces Introductory Example: The Platonic Solids 8.1 Affine Combinations 8.2 Affine Independence 8.3 Convex Combinations 8.4 Hyperplanes 8.5 Polytopes 8.6 Curves and Surfaces 9. Optimization (Online Only) Introductory Example: The Berlin Airlift 9.1 Matrix Games 9.2 Linear Programming-Geometric Method 9.3 Linear Programming-Simplex Method 9.4 Duality 10. Finite-State Markov Chains (Online Only) Introductory Example: Google and Markov Chains 10.1 Introduction and Examples 10.2 The Steady-State Vector and Google''s PageRank 10.3 Finite-State Markov Chains 10.4 Classification of States and Periodicity 10.5 The Fundamental Matrix 10.6 Markov Chains and Baseball Statistics Appendices A. Uniqueness of the Reduced Echelon Form B. Complex Numbers
Copyright Date
2012

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