MATH 39 Linear Algebra I
San Jose State University, Fall 2022Course information [syllabus]
Catalog description: Matrices, systems of linear equations, vector geometry, matrix transformations, determinants, eigenvectors and eigenvalues, orthogonality, diagonalization, applications, computer exercises. Theory in Rn emphasized; general real vector spaces and linear transformations introduced.
Prerequisite: MATH 31 or Math 31X (with a grade of "C-" or better).
Textbook: Linear Algebra and Its Applications [Amazon link], 5th edition, David Lay, Stephen Lay and Jodi McDonald (2015), Pearson. ISBN: 978-0321982384.
Technology requirements:
- Canvas: Assignments and their grades will be posted in Canvas (accessible via https://one.sjsu.edu/).
- Piazza: This course will use Piazza as the bulletin board. Please post all course-related questions there.
- i-Clicker: We will use i-Clicker to perform some in-class activities (such as polling and quizzing).
- Matlab: Matlab can be used to assist calculations in homework. It is freely available for everyone at San Jose State [download].
For more information, see the above-linked course syllabus.
Course material
Slides are continuously being added/updated. You are suggested to download a new copy right before each class (remember to refresh your browser).
| Lectures | Reading | Assignments |
|---|---|---|
| 0: Course introduction [slides] | [MATLAB Onramp] | |
| 1: Systems of linear equations [slides] [worksheet 1a] [1b] | Chapter 1 |
1.1: 3, 11, 16, 18, 25 1.2: 2, 4, 12, 20, 22 1.3: 6, 8, 10, 14, 25 1.4: 2, 4, 5, 8, 9, 12, 13, 16, 22 1.5: 2, 3, 6, 11, 16, 19, 21, 24 1.7: 1, 8, 10, 16, 20 1.8: 4, 7, 10, 12, 17, 30, 31 1.9: 2, 5, 6, 8, 12, 13, 18, 20 |
| 2: Matrix algebra [slides] [worksheet 2] [3] [4] | Chapter 2 |
2.1: 6, 9-12, 18-22, 27 2.2: 3, 6, 7, 11, 12, 13, 18, 19, 32, 35 2.3: 2, 4, 6, 8, 15-21, 27, 28, 34 2.4: 2, 3, 5, 8, 10, 13, 15, 16, 21, 25 2.5: 3, 8, 10, 15, 24, 25, 26 |
| 3: Matrix determinants [slides] [worksheet 5] [6] | Chapter 3 |
3.1: 2, 10, 14, 15, 34-36, 37, 38 3.2: 1-4, 6, 8, 12, 21, 24, 29, 31, 40 3.3: 2, 6, 12, 18 |
|
4: Vector spaces [slides)] [worksheet 7] [8] [9] [10] |
Chapter 4 |
4.1: 5, 8, 15, 18, 21 2.8: 1-4, 5, 7, 8, 10 4.2: 4, 5, 7, 11, 16 4.3: 2, 4, 6, 8, 9, 11, 14, 19 4.4: 1, 4, 8, 17 4.5: 4, 6, 9, 12, 13, 16, 18 4.6: 2, 8, 12, 14, 16, 27, 30 4.7: 8 |
|
5: Eigenvalues and Eigenvectors [slides] [worksheet 11] [12] |
Chapter 5 |
5.1: 6, 8, 9, 14, 18, 19, 25, 26, 27 5.2: 8, 10, 12, 15, 18 |
|
6: Dot product and orthogonality [slides] [worksheet 13] |
Chapter 6 |
6.1: 2, 4, 6, 8, 9, 14, 16, 18, 26, 28 6.2: 2, 4, 7, 9, 12, 14, 15, 17, 20, 29 6.3: 4, 8, 12, 14, 16 6.4: 4, 8, 12 6.5: 4, 8, 10 |
|
7: Diagonalization of symmetric matrices [slides] [worksheet 14] |
Chapter 7 |
7.1: 14, 18, 20 7.4: 4, 12 |
Resources
(to be added)