Syllabus for Math 4242 --- Fall 2009 (MWF 2:30-3:20)

Description:

One semester course on linear algebra. Assuming a basic acquaintance with vectors and matrices, the course goes on to study matrix theory in greater depth as well as some of its applications. Topics include Gauss elimination, matrix algebra, LU factorization, vector spaces, subspaces, dimension, linear transformations, norms and inner products, orthogonality, Gram-Schmidt method, QR factorization, singular values, determinants, eigenvalues, diagonalization.

Text:

Matrix Analysis and Applied Linear Algebra, Carl D. Meyer. We will cover most of the material in Chapters 1-7.

Grades:

There will be grades for quizzes and three midterm exams. All exams and quizzes are open book/notes, calculators allowed.

Quizzes 25 %
Midterm Exams (25% each) 75 %

For general policy statements about grades and academic honesty, go to: Policy Statements, .

Exam Dates:

 Midterm I Monday, October 5
 Midterm II Monday, November 16
 Midterm III Wednesday, December 16

Homework:

Homework will be assigned but not collected. Instead there will be weekly quizzes consisting of problems very similar to the homework problems. If you can do the homework problems you should have no trouble with the quizzes. One quiz score will be dropped to allow for an absence or just a "bad day." To see the assignments, click on the link above.

Approximate Schedule:

 Week  Topic Reading
9/9-9/11 Linear equations, Gauss elimination Chapter 1
9/14-9/18 More on linear system, rank, echelon forms Chapter 2
9/21-9/25 Matrix algebra, inverses 3.1-3.7
9/28-10/2 Sensitivity, elementary matrices, LU factorization 3.8-3.10
10/5-10/9 Midterm I, Vector spaces, subspaces 4.1-4.2
10/12-10/16 Basis, dimension 4.3-4.5
10/19-10/23 Least squares, linear trans., inv. subspaces 4.6-4.9
10/26-10/30 Norms, inner products, orthogonality 5.1-5.4
11/2-11/6 Gram-Schmidt, unitary and orthogonal matrices 5.5-5.6
11/9-11/13 Orthogonal projection, singular value decomp. 5.11-5.13
11/16-11/20 Midterm II, Determinants Chapter 6
11/23-11/25 Eigenvalues, Thanksgiving 7.1
11/30-12/4 Diagonalization, differential equations 7.2-7.4
12/7-12/11 Diag. of normal matrices, quadratic forms 7.5-7.6
12/14-12/16 Jordan form, Midterm III 7.7

Labs:

Here are two do-it-yourself computer labs to see how Matlab can be used to numerically solve linear algebra problems. The links below allow you to download the instructions for the labs which can be done on any computer running Matlab. This is purely for enrichment -- no grades.

Lab 1
Lab 2