
Linear Algebra with Applications
United States Edition
Otto Bretscher(Author)
Pearson (Publisher)
3rd Edition
Published on 23. July 2004
Book
Hardback
496 pages
978-0-13-145334-0 (ISBN)
Article exhausted; check for reprint
Description
For courses in Introductory Linear Algebra.
This text offers the most geometric presentation now available, emphasizes linear transformations as a unifying theme, and is recognized for its extensive and thought-provoking problem sets. While preserving the same table of contents as the previous edition, this revision is the outcome of a careful reflection (and appropriate change) on the wording of each idea.
This text offers the most geometric presentation now available, emphasizes linear transformations as a unifying theme, and is recognized for its extensive and thought-provoking problem sets. While preserving the same table of contents as the previous edition, this revision is the outcome of a careful reflection (and appropriate change) on the wording of each idea.
More details
Edition
3rd edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 254 mm
Width: 203 mm
Weight
1080 gr
ISBN-13
978-0-13-145334-0 (9780131453340)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Book
11/2008
4th Edition
Pearson
€128.74
Article exhausted; check for reprint
Previous edition

Book
03/2001
2nd Edition
Pearson
€89.12
Article exhausted; check for reprint
Content
1. Systems of Linear Equations.
2. Linear Transformations.
3. Subspaces of Rn and Their Dimension.
4. Linear Spaces.
5. Orthogonality and Least Squares.
6. Determinants.
7. Eigenvalues and Eigenvectors.
8. Symmetric Matrices and Quadratic Forms.
9. Linear Differential Equations.
2. Linear Transformations.
3. Subspaces of Rn and Their Dimension.
4. Linear Spaces.
5. Orthogonality and Least Squares.
6. Determinants.
7. Eigenvalues and Eigenvectors.
8. Symmetric Matrices and Quadratic Forms.
9. Linear Differential Equations.