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.
Matrix Analysis and Applied Linear Algebra, Carl D. Meyer. We will cover most of the material in Chapters 1-7.
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, .
Midterm I Wednesday, February 17 Midterm II Wednesday, April 6 Midterm III Friday, May 6 (last class day)
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.
I am writing a Mathematica notebook demonstrating how to use Mathematica for linear algebra. It will be evolving over the course of the semester and the current version can be found here: Mathematica Notebook for Linear AlgebraYou are encouraged to use Mathematica or some other program to do some calculations of your own. You can use Mathematica at the CSE computer labs. To get a CSE computer account go to CSE Accounts. Once you have a CSE lab account, you can also download a copy for your personal computer at: Get Mathematica
Week Topic Reading 1/20-1/22 Linear equations, Gauss elimination Chapter 1 1/25-1/29 More on linear system, rank, echelon forms Chapter 2 2/1-2/5 Matrix algebra, inverses 3.1-3.7 2/8-2/12 Elementary matrices, LU factorization 3.9-3.10 2/15-2/19 Review, Midterm I, Vector spaces, subspaces 4.1-4.2 2/22-2/26 Basis, dimension 4.3-4.4 2/29-3/4 Least squares, linear trans. 4.6-4.8 3/7-3/11 Norms, inner products, orthogonality 5.1-5.4 3/14-3/18 Spring Break !!! 3/21-3/25 Gram-Schmidt, QR factorization, unitary and orthogonal matrices 5.5-5.6 3/28-4/1 Orthogonal reduction, orthogonal decomp., URV^T 5.7,5.11 4/4-4/8 Review, Midterm II, Psuedoinverse 5.12 4/11-4/15 Singular Values, SVD, Applications 5.12 4/18-4/22 Determinants, Eigenvalues, diagonalization Ch. 6, 7.1, 7.2 4/25-4/29 Diag. of normal matrices, quadratic forms 7.5-7.6 5/2-5/6 Review, Midterm III