I. Course Prefix/Number: MAT 260
Course Name: Linear Algebra
Credits: 3 (3 lecture; 0 lab)
III. Course (Catalog) Description
IV. Learning Objectives
2. Understand the concepts of vector spaces, subspaces, basis, independence and dependence, dimension, coordinates, rank of a matrix, inner product.
3. Use the dependency relationship algorithm and the Gram-Schmidt orthogonizational process.
4. Understand linear transformations, range and null space of a linear transformation, the correspondence principle and similarity.
5. Understand properties of the determinant function and the cofactor expansion of determinants.
6. Understand the concepts of eigenvalues and eigenvectors.
7. Understand the concepts of quadratic forms.
V. Academic Integrity
• plagiarism (turning in work not written by you, or lacking proper citation),
• falsification and fabrication (lying or distorting the truth),
• helping others to cheat,
• unauthorized changes on official documents,
• pretending to be someone else or having someone else pretend to be you,
• making or accepting bribes, special favors, or threats, and
• any other behavior that violates academic integrity.
There are serious consequences to violations of the academic integrity policy. Oakton's policies and procedures provide students a fair hearing if a complaint is made against you. If you are found to have violated the policy, the minimum penalty is failure on the assignment and, a disciplinary record will be established and kept on file in the office of the Vice President for Student Affairs for a period of 3 years.
Details of the Code of Academic Conduct can be found in the Student Handbook.
VI. Sequence of Topics
1 Gaussian elimination
2 Homogeneous systems of linear equations
3 Matrices and matrix arithmetic
4 Matrix invertibility
B. Vector Spaces
1. Euclidean n-space
2. Linear independence
3. Basis and dimension
4. Rank of a matrix
5. Inner product spaces
6. Orthonormal bases and projections
C. Linear Transformations
1. Properties, range and null space
2. Matrix representations, products and inverses
1. The determinant function and evaluation
2. Properties of determinants
3. Cofactor expansion
4. Applications including Cramer's Rule
E. Eigenvalues and Eigenvectors
1. Eigenvalues and eigenvectors of linear transformations
F. Quadratic forms
1. Symmetric matrices
G. Recommended Technology
1. Use of technology to perform matrix computations
2. Use of technology to determine matrix products and inverses
3. Use of technology to evaluate determinants
VII. Methods of Instruction
Methods of presentation can include lectures, discussion, experimentation, audio-visual aids, small-group work and regularly assigned homework. Calculators/computers will be used when appropriate. Mathematica, Derive and TI-92 calculators are available for use at the College at no charge.
Course may be taught as face-to-face, media-based, hybrid or online course.
VIII. Course Practices Required
IX. Instructional Materials
Textbooks can also be found at our Mathematics Textbooks page.
A computer algebra system is required.
X. Methods of Evaluating Student Progress
Evaluation methods can include grading homework, chapter or major tests, quizzes, individual or group projects, calculator/computer projects and a final examination.
XI. Other Course Information
If you have a documented learning, psychological, or physical disability you may be entitled to reasonable academic accommodations or services. To request accommodations or services, contact the ASSIST office in the Learning Center. All students are expected to fulfill essential course requirements. The College will not waive any essential skill or requirement of a course or degree program.