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MATH362: Introduction to Linear Algebra
Revised: November 2006
Course Description
Systems of equations, matrices, vector spaces, and linear transformations.
Prerequisites: Math 153, and Math 250. Three semester hours.
Objectives
- To provide clear understanding of the use of matrices in solving
systems of linear equations;
- by use of examples and theory, to provide a thorough understanding
of the concepts of vector spaces and subspaces;
- to acquaint students with linear transformations and eigenvalues.
Text
Gareth Williams, Linear Algebra with Applications, 5th
Edition. Jones and Bartlett (publishers) 2005.
Grading Procedure
Grading procedures and factors influencing course grade are left to
the discretion of individual instructors, subject to general
university policy.
Attendance Policy
Attendance policy is left to the discretion of individual
instructors, subject to general university policy.
Course Outline
Chapter 1: Systems of Linear Equations (3 days)
Sections 1 and 2, with selected applications in section 3 as time allows
Systems of linear equations, Gauss-Jordan elimination, and selected applications (time allowing)
Note: Inclusion of Gaussian elimination (Section 9.1) is also appropriate at this time.
Chapter 2: Matrices (8 days)
Sections 1-4, with selected applications from sections 5-7 as time allows
Matrix operations, properties of matrix operations, symmetric matrices, matrix inverses, and applications (as time allows)
Chapter 3: Determinants (5 days)
Sections 1-4
Introduction to determinants, properties of determinants, evaluating determinants, and determinants with systems of equations
Chapter 4: The Vector Space Rn (5 days)
Sections 1-3; section 4 is optional
Introduction to vectors and vector operations in Rn, dot product, norm, angle, and distance.
Also, an introduction to linear transformations
Note: Coverage of Section 4.3 (and 4.4, if covered) might be delayed, and introduced with Chapter 7.
Chapter 5: General Vector Spaces (10 days)
Sections 1-7
General vector spaces, subspaces, linear dependence and independence, bases and dimension, rank of a matrix, orthonormal vectors,
and vector projections.
Chapter 6: Eigenvalues and Eigenvectors (3 days)
Section 1, with optional coverage of other sections (section 3 recommended if time allows)
Eigenvalues and eigenvectors. Diagonalization of matrices and/or other applications as time allows.
Chapter 7: Linear Transformations (2 or more days)
Section 1, and additional material as time allows
Linear transformations, kernel, and range. Coverage of additional material in this chapter is encouraged, if time remains at the end of the semester.
Note: Coverage of this chapter might be combined with sections 4.3 and 4.4
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Note: At appropriate places in this course, time should be allotted to
elaborate on the historical aspects relevant to the subject.
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