C-309 Wells Hall

Professor Thomas H. Parker

A-346 Wells Hall tel: 353-8493

parker@math.msu.edu

Tentative Office hours:

Monday: 1:30 -2:30

Wednesday 3-4

Friday 2-3

and by appointment (email to set up time).

Goals: This is a second course Linear Algebra intended for physics, engineering, statistics, computer science, and mathematics majors (and graduate students).

After calculus, Linear Algebra is the most useful branch of mathematics, with innumerable applications in statistics, computer science, engineering, physics, economics and in mathematics itself. It is an appealing combination of algebra and geometry that is mathematically "clean": the definitions, theorems and proofs are often simple, illuminating, and are readily translated into powerful computational methods.

Math 415 covers the theory needed to understand a wide range of applications. Numerous specific applications are included.

Prerequisites: A previous Linear Algebra course, or a familiarity with linear algebra.

Textbook: *Applied Linear Algebra* by
L. Sadun. We will cover most of the book this semester.

Syllabus: Math 415 Syllabus (pdf)

Recommended download: *Linear
Algebra done wrong* by S. Treil. A free online book (266 pages)
with a clean presentation. Some assignments will come from this text.
Download at this
page and
read a description here.

Additonal Resources: The following textbooks are helpful. They -- and the Sadun textbook -- are on reserve in the Mathematics Library.

*Linear Algebra with Applications*by Steven Leon.*Linear Algebra with Applications*by Otto Bretscher.

Homework Sets: **HW1** HW2 HW3 HW4 HW5 **HW6** HW6Solutions **HW7** **HW8** **HW9** **HW10** **HW11** **HW12**

Handouts: Sadun9-13 **Notes on Inner Products** **Sampling** **PCA**

Web Calculators: This
site calculates
eigenvalues and eigenvectors, **this
site** is useful for other matrix calculations, and **this
site** has Fourier Series demonstations.

Exams: **Midterm
Review Sheet**
**Midterm
Solutions**
**Final Exam**

Video lectures: This MIT open online course on Linear Algebra (with Prof. G. Strang) assumes no previous knowledge of linear algebra, so may be useful for review. Prof. Strang's approach emphasizes the applications of linear algebra to numerical analysis.

Homework: There will be weekly homework assignments.