Back to Prof. Calhoun's Homepage

Introduction to Linear Algebra (Math 301)


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.

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 Monday/Wednesday 12:00-1:15
Place Mathematics 104
Office Hours Tuesday 1:30-3:00
Prerequesites Math 175

Return to top of page


Required textbook and other resources

Return to top of page


Lectures

We will stick the following schedule as much as possible.

Week #1 (Jan. 13)
Monday --  Introduction to Linear Algebra; Sections 1.1
Wednesday --  Section 1.2 : Linear Systems and Matrices

Week #2 (Jan. 20)
Monday --  Martin Luther King Day (no class)
Wednesday --  Section 1.2 - cont.

Week #3 (Jan. 27)
Monday --  Section 1.3 : Applications
Wednesday --  Section 2.1 : Vectors; Section 2.2 : Span

Week #4 (Feb. 3)
Monday --  Section 2.3 : Linear Independence
Wednesday --  Section 2.3 : Linear Independence (cont)
Other items of interest :
Practice Sheet #1 (Feb-03-2020.pdf)

Week #5 (Feb. 10)
Monday --  Section 3.1 : Linear transformations
Other items of interest :
Practice Sheet #2 (Feb-10-2020.pdf)
Wednesday --  Section 3.2 : Matrix algebra
Other items of interest :
Practice Sheet #3 (Feb-12-2020.pdf)
Review for Exam #1 (review_exam1.pdf)

Week #6 (Feb. 17)
Monday --  President's Day (no class)
Wednesday --  Midterm #1

Week #7 (Feb. 24)
Tuesday --  Section 3.3 : Matrix Inverse
Thursday --  Section 3.5 : Markov chains

Week #8 (Mar. 2)
Monday --  Markov chains (continued)
Wednesday --  Markov Chains (continued)
Other items of interest :
Practice Sheet #4 (practice_04.pdf)

Week #9 (Mar. 9)
Monday --  Section 4.1 : Introduction to subspaces
Wednesday --  Section 4.2 : Basis and dimension

Week #10 (Mar. 16)
Monday --  Section 4.3 : Row and column spaces
Other items of interest :
Practice Sheet #6 (practice_06.pdf)
Wednesday --  Section 4.3 : Row and column spaces (cont.)
Other items of interest :
Practice Sheet #7 (practice_07.pdf)
Practice Sheet #8 (practice_08.pdf)

Week #11 (Mar. 30)
Monday --  Section 5.1 : Determinants
Other items of interest :
Practice Sheet #9 (practice_09.pdf)
Wednesday --  Section 5.2 : Properties of Determinants

Week #12 (Apr. 6)
Monday --  Midterm #2
Wednesday --  5.3: Applications of determinants

Week #13 (Apr. 13)
Monday --  Section 6.1 : Eigenvalues and Eigenvectors
Wednesday --  Section 6.2 : Diagonalization
Other items of interest :
Practice Sheet #10 (practice_10.pdf)
Practice Sheet #11 (practice_11.pdf)

Week #14 (Apr. 20)
Monday --  Section 6.2 : Diagonalization (cont.)
Wednesday --  Section 6.3 : Complex Eigenvalues and Eigenvectors

Week #15 (Apr. 27)
Monday --  Review : Eigenvalues and Eigenvectors
Wednesday --  General Review
Other items of interest :
Final review (final_review.pdf)

Return to top of page


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 TBA

Assignment :
This assignment is on WebAssign

Return to top of page


Exams

We will have two midterms and one final exam

Midterm #1 Date: Wednesday, February 19

Midterm #2 Date: Monday, April 6th

Final Date: Monday, May 4

The final is 12:00-2:00 in our regular classroom


You can find the Final Exam calendar here.

Return to top of page


Grading policy

Homework will count for 25% of your final grade, and the two midterms and final will count for 75%. 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%.

Return to top of page