This versatile undergraduate text can be used in a variety of courses in linear algebra. It contains enough material for a two-semester course, and it also serves as a support text and reference. Chapter Ten, on linear programming, will be of special interest to students of business and economics. A balanced combination of formal theory and related computational techniques, this treatment begins with the familiar problem of solving a system of linear equations. Subsequent chapters explore linear spaces and mappings, matrices, determinants, inner product spaces, scalar-valued functions, and linear differential equations. The author introduces metric notions of Euclidean space at an early stage and employs the computational technique of Gaussian elimination throughout the book. Solutions to selected exercises appear at the end.
About the Author
The late Daniel T. Finkbeiner II was a Professor of Mathematics at Kenyon College for 30 years and the author of three successful mathematics texts.
Table of Contents
1. Linear Equations
2. Linear Spaces
3. Linear Mappings
6. Equivalence Relations on Rectangular Matrices
7. A Canonical Form for Similarity
8. Inner Product Spaces
9. Scalar-Valued Functions
10. Application: Linear Programming
11. Application: Linear Differential Equations
Solutions for Selected Exercises
Most Helpful Customer Reviews
There are many books about linear algebra but this is the only one I've seen that derives basic matrix operations from principles of linear algebra. Matrix operations such as transposing or finding a determinant are really disguised operations in linear algebra. This book makes the connection.