Math 415 Spring 2012

Applied Linear Algebra

MWF 12:40 -- 1:30
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.

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.