# Elementary Linear Algebra

**Textbook:** Introductory Linear Algebra: An Applied
First Course (8th ed.), by B. Koleman and D. Hill.

We will cover Chapters 14 and 68.

**Course Description: **Matrices (properties of
matrices, matrix algebra and operations, determinants, in-

verse of a matrix eigenvalues and eigenvectors), methods of solving systems of
linear equations (Gaussian

elimination, Gauss-Jordan elimination, Cramers Rule), vectors (linear
independence, span, basis and di-

mension), applications (coding, computer graphics, electrical circuits).

**Attendance Policy: **If you have three or fewer
unexcused absences during the semester, your lowest test

score and your lowest quiz score will be dropped. If you miss a class, you must
contact me with a reason

as soon as possible in order to have the absence excused. I may not excuse your
absence if you are absent

excessively and/or not performing adequately in the class.

**Homework: **I will assign 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 five 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).

**Final: **There will be a cumulative final exam worth
180 points on Friday, December 8, 8:0010:00AM.

**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 (740). Your letter grade will
be determined according the

following grading scale: A: 88100, B: 7687, C: 6475, D: 5263, F: 051.

**Withdrawal: **October 6 is the last day to withdraw
from the course with a grade of W.

**Testing Schedule**

8/25 | Quiz 1 |

9/1 | Test 1 |

9/15 | Quiz 2 |

9/22 | Test 2 |

10/6 | Quiz 3 |

10/13 | Test 3 |

10/27 | Quiz 4 |

11/3 | Test 4 |

11/17 | Quiz 5 |

11/28 | Test 5 |

12/8 | Final exam (8:00AM) |

**Academic Dishonesty Policy: **Any student who engages
in any form of academic dishonesty will receive

an F for the course. 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 matrix operations.

2. How to compute the inverse or determinant of a square matrix.

3. How to express linear systems of equations in matrix form.

4. How to solve systems of linear equations using Gaussian elimination and Gauss-Jordan elimination.

5. How to solve systems of linear equations using Cramers Rule.

6. The basic properties of real vector spaces and
subspaces including properties such as linear indepen-

dence, span, basis, rank.

7. How to analyze linear transformations.

8. How to compute eigenvalues and eigenvectors of a square matrix.

9. How to diagonalize a square matrix.

10. Use MATLAB to perform basic matrix operations and solve linear systems.