Elementary Linear Algebra

Office Hours:

(*2:303:30 in 302 Boyd)

If you would like to see me but cannot come during one of these times, please call …first or make an appointment.

Textbook: Elementary Linear Algebra : A Matrix Approach, by Spence, Insel, and Friedberg. We will cover
Chapters 13 and parts of 46.

Course Description: Methods of solving systems of linear equations (Gaussian elimination, Gauss-Jordan
elimination, Cramers Rule, LU-decomposition), vectors ( dot product , projection, linear independence, span,
basis and dimension), matrices ( properties of matrices , matrix algebra , determinants, eigen values and eigen -
vectors), linear transformations, applications.

Attendance Policy: If you have four or fewer unexcused absences during the semester, your lowest test
score and lowest quiz score will be dropped. If you miss a class, you must contact me with a reason within
two days of the absence in order to have the absence excused. I may not excuse your absence if I feel that
you are absent excessively and not performing adequately in the class.

Homework: I will as sign homework exercises after each section. These problems will not be graded, but
you may be quizzed on them. I will allow some time during class to discuss the problems and I encourage
you to use my office hours if you have any questions about them.

Lab Assignments: There will be eight computer lab assignments (using MATLAB) given throughout the
semester. They will be worth 10 points each.

Tests and Quizzes: There will be six 30-minute quizzes, worth 40 points each, consisting of problems from
homework. There will be five 50-minute tests, worth 80 points each. (See schedule below for test and quiz
dates.)

Rescheduling Tests and Quizzes: If you have a valid reason for missing a test or quiz, you may be
allowed to reschedule, but you must make arrangements with me at least one week in advance of the test or
quiz. If you miss a test or quiz and have not made arrangements with me to take it at another time, you
will receive a zero (This may be used as your dropped score).

Grading Errors: In order to have a grade changed as a result of a grading error, you must bring the error
to my attention within one week of the time you received the graded test or quiz.

Final: There will be a cumulative final  exam worth 200 points.

Grading: Your numerical grade will be your total points (on labs, quizzes, tests, and the …final) as a
percentage of the total number of possible points (800). Your letter grade will be de termined according the
following grading scale: A: 88100, B: 7687, C: 6475, D: 5263, F: 051.

Withdrawal: March 3 is the last day to with draw from the course with a grade of W.

First Homework Assignment: p.9 #1, 5, 7, 9, 10, 35, 43, 44.

Testing Schedule

Academic Dishonesty Policy: Any student who engages in any form of academic dishonesty will receive
an F for the course. The incident will also be reported to the Office of Student Affairs so that they can
determine if further disciplinary action is warranted. Academic dishonesty is defined as one or more of the
following:

1. Use of unauthorized information during a test, quiz, or exam.
2. Copying material from another students paper during a test, quiz, or exam.
3. Giving or receiving information during a test, quiz, or exam.
4. Giving information about the content of a test, quiz, or exam to a student who will be taking the test
at a later time.
5. Obtaining unauthorized information about the content of a test, quiz, or exam before taking it.
6. Copying all or part of another students work on a lab assignment.

Learning Outcomes: The student will have an understanding of:

1. How to perform basic vector ope rations .
2. How to compute the inverse or determinant of a square matrix.
3. How to compute the LU-decomposition of a square matrix.
4. How to express linear systems of equations in matrix form.
5. How to solve systems of linear equations using Gaussian elimination and Gauss -Jordan elimination.
6. How to solve systems of linear equations using Cramers Rule.
7. The geometric properties of vectors.
8. The basic properties of real vector spaces and subspaces including properties such as linear indepen-
dence, span, basis, rank.
9. How to analyze linear transformations.
10. How to compute eigenvalues and eigenvectors of a square matrix.
11. How to diagonalize a square matrix.
12. Use MATLAB to perform basic matrix operations .