Courses on linear algebra and numerical analysis need each other. Often
NA courses have some linear algebra topics, and LA courses mention some
topics from numerical analysis/scientific computing. This text merges
these two areas into one introductory undergraduate course. It assumes
students have had multivariable calculus. A second goal of this text is
to demonstrate the intimate relationship of linear algebra to
applications/computations.
A rigorous presentation has been maintained. A third reason for writing
this text is to present, in the first half of the course, the very
important topic on singular value decomposition, SVD. This is done by
first restricting consideration to real matrices and vector spaces. The
general inner product vector spaces are considered starting in the
middle of the text.
The text has a number of applications. These are to motivate the student
to study the linear algebra topics. Also, the text has a number of
computations. MATLAB(R) is used, but one could modify these codes to
other programming languages. These are either to simplify some linear
algebra computation, or to model a particular application.