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Linear Algebra : A First Course in Pure and Applied Math by Edgar G. Goodaire (2003, Hardcover)
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bk17: Linear Algebra: A First Course in Pure and Applied Math, Goodaire, Edgar G.
- Buy It Nowbk17: Linear Algebra: A First Course in Pure and Applied Math, Goodaire, Edgar G
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About this product
Product Information
For freshman/sophomore-level courses in linear algebra. This innovative new way of teaching a first linear algebra course stresses an "Active Reading" theme that teaches students to reach mathematics. A secondary theme of the text is much more applied: solving least square solutions to AX = b.Product Identifiers
PublisherPrentice Hall PTR
ISBN-100130470171
ISBN-139780130470171
eBay Product ID (ePID)2316044
Product Key Features
Number of Pages656 Pages
LanguageEnglish
Publication NameLinear Algebra : a First Course in Pure and Applied Math
Publication Year2003
SubjectAlgebra / Linear, Algebra / General
TypeTextbook
Subject AreaMathematics
AuthorEdgar G. Goodaire
FormatHardcover
Dimensions
Item Height1.1 in
Item Weight43.3 Oz
Item Length9.4 in
Item Width8.3 in
Length9.4in
Additional Product Features
LCCN2002-044551
Dewey Edition21
Target AudienceCollege Audience
IllustratedYes
Dewey Decimal512/.5
Lc Classification NumberQa184.2.G66 2002
Table of Content(NOTE: Each chapter concludes with Review Exercises. ) 1. The Geometry of the Plane and 3 Space. Vectors. Length and Direction. Lines, Planes, Cross Product. Projections. Euclidean n -space. 2. Matrices and Linear Equations. The Algebra of Matrices. The Inverse and Transpose. Systems of Linear Equations. Homogeneous Systems and Linear Independence. The LU Factorization of a Matrix. LDU Factorizations. Finding the Inverse of a Matrix. 3. Determinants and Eigenvalues. The Determinant of a Matrix. Properties of Determinants. The Eigenvalues and Eigenvectors of a Matrix. Similarity and Diagonalization. 4. Vector Spaces. The Theory of Linear Equations. Basic Terminology and Concepts (Mostly Review). Basis and Dimensions; Rank and Nullity. One-sided Inverses. 5. Linear Transformations. Fundamentals. Matrix Multiplication Revisited. The Matrices of a Linear Transformation. Changing Coordinates. 6. Orthogonality. Projection Matrices and Least Square Approximation. The Gram-Schmidt Algorithm and QR Factorization. Orthogonal Subspaces and Complements. The Pseudoinverse of a Matrix. 7. The Spectral Theorem. Complex Numbers and Vectors. Complex Matrices. Unitary Diagonalization. The Orthogonal Diagonalization of Real Symmetric Matrices. The Singular Value Decomposition. 8. Applications. Data Fitting. Linear Recurrence Relations. Markov Processes. Quadratic Forms and Conic Sections. Graphs. Show and Prove. Things I Must Remember. Solutions to Selected Exercises. Solutions to True/False Questions. Glossary. Index.
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Ratings and Reviews
Most relevant reviews
- May 31, 2017
Linear Algebra
An easy to understand intro. to the subject. Not so old as to be archaic.Verified purchase: YesCondition: Pre-owned
