Chuck Iverson (http://www.civerson.com, iverson@smccd.edu)
Building 22, Room 118
12:45-2:00 pm MW
Prerequisites
Physics 250 and Math 252, both with a grade of C or better.
Materials
- Linear Algebra (2nd Edition) by Poole (0-534-99845-5)
Grading
Your grade will be based on:
- Homework and Exercises (30%)
- Exams and Quizzes (70%)
Course Description
Study of vectors, systems of linear equations, the algebra of matrices, determinants, eigenvalues and eigenvectors, vector spaces, inner products and least-squares.
Homework
Reading the textbook and doing the assigned exercises are the most important work students can do between classes to insure understanding of concepts and to develop skill in applying problem solving techniques. Consequently, exercises and labs are collected and contribute 30% to the final grade. Late assignments get a maximum of half credit. Each set of exercises or problems must have the following information printed at the top, right corner of the page: student name, section number, page numbers, exercise numbers and date. For example:
- Your Name
- Section 1.5
- pp. 57-59 (1-29, odd)
- 9/25/08
Exams
Frequent quizzes, three midterm exams and a final exam on the last chapter will be given during the semester. Each midterm exam will cover two chapters. The final exam will cover one chapter. You may have one sheet of notes for each chapter covered. See the tentative schedule below for the dates of the exams.
Make-Up Exams
A make-up exam will be offered to any student who scores less than his or her homework average on a particular exam. Before taking a make-up exam, a student must meet with me to review his or her original exam. A make-up exam score will be limited to a student's current homework average. A make-up exam score will replace an original exam score only if the make-up exam score is higher.
Expectations
I can help you succeed in this class, but I can't succeed for you. In this class you're expected to be responsible for your own academic success.
- That means you are expected to attend class and to arrive on time (2 lates equals 1 absence, 7 absences leads to a drop).
- If you're going to miss class, you should notify me ahead of time, either by phone or email.
- You are expected to contribute to class discussions and to ask questions when something is not clear.
- You are expected to do your homework assignments before the class when they are due and to seek help from me or your classmates or Nancy Ward if you are having difficulty completing them.
- You should check WebAccess (http://smccd.mrooms.net/) for assignments and class notes programs if you miss class.
- You are expected to see me during office hours for additional help or to take make-up exams.
All class assignments, exam solutions and special notes will be posted on the web after class (with links on WebAccess). You are invited to share questions, answers, ideas, opinions, and suggestions by posting them on WebAccess.
Instructor's Fall 2008 Class Schedule
My class schedule, below, shows when and where I'm on campus. The best way to contact me if I'm not on campus is via email. I check my email several times a day. I have my email automatically sorted by the first 4 characters in the subject field. For this class, the subject line of the email should begin with M270.

Tentative Topic Schedule
| Monday | Wednesday |
|---|---|
| 8/18 - 1.0 Racetrack Game 1.1 Geometry and Algebra of Vectors 1.2 Length and Angle: Dot Product |
8/20 - 1.3 Lines and Planes 1.4 Code Vectors and Modular Arithmetic |
| 8/25 - 2.0 Triviality 2.1 Introduction to Systems of Linear Equations 2.2 Direct Methods for Solving Linear Systems |
8/2 - 2.2 Direct Methods for Solving Linear Systems |
| 9/1 - Labor Day Holiday | 9/3 - 2.3 Spanning Sets and Linear Independence 2.4 Applications |
| 9/8 - Chapter 1-2 Review | 9/10 - Chapter 1-2 Exam |
| 9/15 - 3.0 Matrices in Action 3.1 Matrix Operations 3.2 Matrix Algebra |
9/17 - 3.3 Inverse of a Matrix |
| 9/22 - 3.4 The LU Factorization | 9/24 - 3.5 Subspaces, Basis, Dimension and Rank |
| 9/29 - 3.6 Introduction to Linear Transformations 3.7 Applications |
10/1 - 4.0 A Dynamical System on Graphs 4.1 Introduction to Eigenvalues and Eigenvectors |
| 10/6 - 4.2 Determinants 4.3 Eigenvalues and Eigenvectors of n x n Matrices |
10/8 - 4.4 Similarity and Diagonalization 4.6 Applications |
| 10/13 - Chapter 3-4 Review | 10/15 - Chapter 3-4 Exam |
| 10/20 - 5.0 Shadows on a Wall 5.1 Orthogonality in R^n 5.2 Orthogonal Complements and Orthogonal Projections |
10/22 - 5.3 The Gram-Schmidt Process and the QR Factorization |
| 10/27 - 5.4 Orthogonal Diagonalization of Symmetric Matrices 5.5 Applications |
10/29 - 6.0 Fibonacci in (Vector) Space 6.1 Vector Spaces and Subspaces |
| 11/3 - 6.2 Linear Independence, Basis and Dimension 6.3 Change of Basis |
11/5 - 6.4 Linear Transformations |
| 11/10 - Veteran's Day Holiday | 11/12 - 6.5 The Kernel and Range of a Linear Transformation |
| 11/17 - 6.6 The Matrix of a Linear Transformation 6.7 Applications |
11/19 - Chapter 5-6 Review |
| 11/24 - Chapter 5-6 Exam | 11/26 - 7.0 Taxicab Geometry 7.1 Inner Product Spaces |
| 12/1 - 7.2 Norms and Distance Functions |
12/3 - 7.3 Least Squares Approximation |
| 12/8 - 7.4 Singular Value Decomposition 7.5 Applications |
12/10 - Chapter 7 Review |
| 12/15 - 2:10-4:40 Chapter 7 Exam |