Introduction to Linear Algebra (Math 301, Fall 2020)
Linear algebra from a matrix perspective with applications from the applied sciences. Topics include the algebra of matrices, methods for solving linear systems of equations, eigenvalues and eigenvectors, matrix decompositions, and linear transformations. Prerequisites: Math 170, Math 175.
- Learn how to convert a system of linear equations to a matrix equation
- Learn how to manipulate matrix equations to solve for a solution vector
- Learn to solve underdetermined linear systems
- Linear independence
- Finite vector spaces and subspaces
- Linear transformations
- Computing eigenvalues and eigenvectors
- Applications!
- Basic course information
- Required textbook and other resources
- Lectures
- Homework assignments
- Exams
- Grading policy
Send me an e-mail
Please send me an e-mail at donnacalhoun@boisestate.edu so that I can compile an e-mail list for the class. At the very least, include a subject header that says "Math 301". You may leave the message area blank, if you wish, or send me a short note about what you hope to get out of this course.
Basic course information
| Instructor | Prof. Donna Calhoun |
| Office | Mathematics 241A |
| Time | Wednesday/Friday 9:00-10:15 |
| Place | Virtual - See BlackBoard for Zoom link |
| Office Hours | Wednesday 12:00-1:30 |
| Prerequesites | Math 175 |
Required textbook and other resources
- Linear Algebra with Applications, Second Edition, by Jeffrey Holt. W. H. Freeman, (2017) (required).
- Web-Assign, by . (required).
Lectures
We will stick the following schedule as much as possible.
| Week #1 (Aug. 24) |
Wednesday
(8/26) --
Introduction to Linear Algebra; Sections 1.1
Friday
(8/28) --
Section 1.1 (cont.)
|
| Week #2 (Aug. 31) |
Wednesday
(9/2) --
Section 1.1 (cont.)
Friday
(9/4) --
Section 1.3 - Applications
|
| Week #3 (Sep. 7) |
Wednesday
(9/9) --
Section 1.3 : Applications
Friday
(9/11) --
Section 2.1 : Vectors
|
| Week #4 (Sep. 14) |
Wednesday
(9/16) --
Section 2.2 : Span
Friday
(9/18) --
Section 2.2 : Span (cont)
|
| Week #5 (Sep. 21) |
Wednesday
(9/23) --
Section 2.3 : Linear independence
Friday
(9/25) --
Section 2.3 : Linear independence (cont.)
|
| Week #6 (Sep. 28) |
Wednesday
(9/30) --
Review for Midterm #1
Friday
(10/2) --
Midterm #1
|
| Week #7 (Oct. 5) |
Wednesday
(10/7) --
Section 3.1 : Linear transformations
Friday
(10/9) --
Section 3.2 : Matrix Algebra
|
| Week #8 (Oct. 12) |
Wednesday
(10/14) --
Section 3.2 : Matrix Algebra (cont.)
Friday
(10/16) --
Section 3.3 : Matrix inverse
|
| Week #9 (Oct. 19) | |
| Week #10 (Oct. 26) | |
| Week #11 (Nov. 2) | |
| Week #12 (Nov. 9) |
Wednesday
(11/11) --
Review for Midterm #2
Friday
(11/13) --
Midterm #2
|
| Week #13 (Nov. 16) | |
| Week #14 (Nov. 30) | |
| Week #15 (Dec. 7) | |
Homework assignments
Homework assignments are to be done on WebAssign are due at 11:59PM of the due date listed in WebAssign.
| Homework #1 |
Due Tuesday 9/8 (Midnight) This assignment is on WebAssignComments : Section 1.1 and 1.2 |
| Homework #2 |
Due Tuesday 9/15 (Midnight) This assignment is on WebAssignComments : Section 1.3 and 2.1 |
| Homework #3 |
Due Friday 9/25 (Midnight) This assignment is on WebAssignComments : Section 2.2 and 2.3 |
| Homework #4 |
Due Friday 10/14 (Midnight) This assignment is on WebAssignComments : Section 3.1 and 3.2 |
| Homework #5 |
Due Sunday 10/25 (Midnight) This assignment is on WebAssignComments : Section 3.3 |
Exams
We will have two midterms and one final exam
| Midterm #1 | Date: Friday, October 2 |
| Midterm #2 | Date: Friday, November 13 |
| Final | Date: Wednesday, December 16 The final is 9:30-11:30 |
You can find the Final Exam calendar here.
Grading policy
Homework will count for 20% of your final grade, and the two midterms and final will count for 25%. An additional 5% of your grade will be based on in class participation. A 90% and above will earn you an A, between 80% and 90% will earn you at least a B, between 70% and 80% will be at least a C, and below 60% will be a D or F. If there is any deviation from this grading policy, it will be to lower the percentages, i.e. you could still earn an A with less than 90%, but you will never need more than 90%.