Math 270

Linear Algebra

Instructor

Chuck Iverson (http://www.civerson.com, iverson@smccd.edu)

Class Location and Meeting Times

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.
WebAccess

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.

F08Schedule

Tentative Topic Schedule

MondayWednesday
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