SELECTED
TOPICS IN MODERN ALGEBRA II
Ma
623
1. Course Description
This
course studies: vector spaces, Euclidean space, sets of linear transformations
and matrices, and bilinear and quadratic forms. Selected Topics in Modern
Algebra I is not a prerequisite.
2. Goals of the Course
1. To investigate linear algebra topics from an
axiomatic viewpoint.
2.
To introduce the students to higher
mathematics concepts
3.
To prepare students for graduate studies
at the doctoral level
4.
To demonstrate that linear algebra is a
very useful subject with wonderful applications in many fields.
3. Instructional Procedures
1. Lecture/discussion
2. Small group and independent study
3.
Use of computer software and graphing
calculators
4.
Assigned written presentation of an
application of linear algebra.
4. Course Content
1.
Systems of Linear Equations
a.
Introduction to Systems of Linear
Equations
b.
Gaussian Elimination and Gauss-Jordan
Elimination
c.
Applications of Systems of Linear
Equations
2.
Matrices
a.
Operations with Matrices
b.
Properties of Matrix Operations
c.
The Inverse of a Matrix
d.
Elementary Matrices
e.
Applications of Matrix Operations
3.
Determinants
a.
The
Determinant of a Matrix
b.
Evaluation of a Determinant Using
Elementary Operations
c.
Properties of Determinants
d.
Applications of Determinants
4.
Vector Spaces
a.
Vectors in Rn
b.
Vector Spaces
c.
Subspaces of Vector Spaces
d.
Spanning Sets and Linear Independence
e.
Basis and Dimension
f.
Rank of a Matrix and Systems of Linear
Equations
g.
Coordinates and Change of Basis
h.
Applications of Vector Spaces
5.
Inner Product Spaces
a.
Length and Dot Product in Rn
b.
Inner Product Spaces
c.
Orthonormal Bases: Gram-Schmidt Process
d.
Mathematical Models and Least Squares
Analysis
e.
Applications of Inner Product Spaces
6.
Linear Transformations
a.
Introduction to Linear Transformations
b.
Kernel and Range of a Linear
Transformation
c.
Matrices for Linear Transformations
d.
Transition Matrices and Similarity
e.
Applications of Linear Transformations
7.
Eigenvalues and Eigenvectors
a.
Eigenvalues and Eigenvectors
b.
Diagonalization
c.
Symmetric Matrices and Orthogonal
Diagonalization
d.
Applications of Eigenvalues and Eigenvectors
8.
Numerical
Methods (optional)
a.
Gaussian Elimination with Partial
Pivoting
b.
Iterative Methods for Solving Linear
Systems
c.
Power Method for Approximating
Eigenvalues
d.
Applications of Numerical Methods
5.
Evaluation Measures for Determining
Students’ Grades
1. Tests 44%
2. Application project 22%
3. Final exam 34%
Note: Individual instructors may weigh
evaluation measures differently.
6.
Bibliography
A.
Required Text
Larson,
Roland E. and Edwards, Bruce H., Elementary
Linear Algebra, 3d ed, D. C. Heath and Company, Lexington, MA, 1996.
Note: In mathematics courses it is usually preferable to have a
designated textbook which helps to focus the discussion and standardize the
language and symbolism.
B.
Additional Required
None
C.
Supporting Bibliography
Apostol,
Tom M., Linear Algebra : A First Course, With
Applications
to Differential Equations, John Wiley & Sons,
Bhatia, Rajendra, Matrix
Analysis (Graduate Texts in Mathematics, 169), Springer Verlag, 1996
Curtis, Morton L., Abstract
Linear Algebra, (Universitext), Springer Verlag, 1990
Evans, Benny and Johnson,
Jerry, Linear Algebra With Derive , John Wiley & Sons,
Gelfand,
I.M., A. Shenitzer (Translator), I. M. Gel'fand, Lectures on Linear Algebra ,
Halmos, Paul Richard, Finite-Dimensional
Vector Spaces, Springer Verlag, 1986
Lax, Peter D., Linear
Algebra, (Pure and Applied Mathematics), John Wiley & Sons,
Roman,
Steven, Advanced Linear Algebra, (Graduate Texts in Mathematics, 135),
Springer Verlag, 1992
D.
Relevant Periodical Sources
None
E.
Relevant
Software
Derive
MatrixPad
F.
Other
TI-82 or TI-83 Graphing Calculator