Class Learning

Linear Algebra: Theory and Applications, Second Edition

  • Buy nowSecond Edition
    2012
    ISBN: 9781449613525
    £43.99
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    Second Edition
    ISBN: 9781449613525
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Ward Cheney & David Kincaid

Ward Cheney and David Kincaid have developed Linear Algebra: Theory and Applications, Second Edition, a multi-faceted introductory textbook, which was motivated by their desire for a single text that meets the various requirements for differing courses within linear algebra.

For theoretically-oriented students, the text guides them as they devise proofs and deal with abstractions by focusing on a comprehensive blend between theory and applications. For application-oriented science and engineering students, it contains numerous exercises that help them learn and understand not only vector spaces, matrices, and linear transformations, but also uses of software tools available for use in applied linear algebra.

Using a flexible design, it is an ideal textbook for instructors who wish to make their own choice regarding what material to emphasise, and to accentuate those choices with homework assignments from a large variety of exercises, both in the text and online.

Features & Benefits:

- New General Exercises and Computer Exercises have been added to nearly all sections throughout the text.

- Thousands of exercises, both True/False and multiple-choice, are included online and within the Student Study Guide.
   
- The authors encourage students to learn one of the powerful mathematical software tools, such as Matlab, Maple, or Mathematica to assist in solving exercises.
  
-  Numerous examples throughout the text show how problems from engineering, biology, natural science, and demography can be solved using linear algebra.

- A Student Solutions Manual and Study Guide provides worked solutions to selected exercises from the text as well as additional exercises.

Table of Contents:

Chapter  1  Systems of Linear Equations
Chapter  2  Vector Spaces and Transformations
Chapter  3  Matrix Operations
Chapter  4  Determinants
Chapter  5  Vector Spaces
Chapter  6  Eigensystems
Chapter  7  Inner Product Vector Spaces
Chapter  8  Additional Topics


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