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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, vector spaces, linear transformations, least squares, and numerical techniques. 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 Tuesday/Thursday 10:30-11:45
Place Engineering Building Rm 313
Office Hours Wednesday 1:30PM-3:30PM, or by appointment
Prerequesites Math 175

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Required textbook and other resources

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Lectures

We will stick the following schedule as much as possible.

Week #1 (Jan. 8)
Tuesday --  Introduction to Linear Algebra; Sections 1.1
Thursday --  Section 1.2 : Linear Systems and Matrices

Week #2 (Jan. 15)
Tuesday --  Section 1.3 : Applications of linear systems
Thursday --  Section 2.1 : Vectors

Week #3 (Jan. 22)
Tuesday --  Section 2.2 : Span
Thursday --  More on Span; Section 2.3 : Linear Independence

Week #4 (Jan. 29)
Tuesday --  Section 2.3 : Linear Independence
Thursday --  Section 3.1 : Linear Transformation

Week #5 (Feb. 5)
Tuesday --  Linear transformations (continued)
Thursday --  Section 3.2 : Linear Algebra

Week #6 (Feb. 12)
Tuesday --  Review for Midterm #1
Thursday --  Midterm #1

Week #7 (Feb. 19)
Tuesday --  3.4 : LU Factorization
Thursday --  3.4 : LU (Continued)

Week #8 (Feb. 26)
Tuesday --  Section 4.1 : Introduction to Subspaces; Section 4.2 : Basis and Dimension
Lecture slides :
The matrix inverse  (pdf)
Thursday --  Section 4.2 : Basis and Dimension

Week #9 (Mar. 6)
Tuesday --  Midterm #2
Thursday --  No Class!

Week #10 (Mar. 12)
Tuesday --  Section 5.1 : The Determinant Function
Thursday --  Section 5.2 : Properties of the Determinant

Week #11 (Mar. 19)
Tuesday --  Section 5.3 : Applications of the Determinant
Thursday --  TBA

Week #12 (Apr. 2)
Tuesday --  Section 6.1 : Eigenvalues and Eigenvectors
Thursday --  Section 6.2 : Diagonalization

Week #13 (Apr. 9)
Tuesday --  Section 6.3 : Complex eigenvalues and eigenvectors
Thursday --  Section 6.4 : Differential Equations

Week #14 (Apr. 16)
Tuesday --  TBA
Thursday --  Midterm #3

Week #15 (Apr. 23)
Tuesday --  Review for Final
Thursday --  Review for Final

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Homework assignments

Homework assignments are to be done on WebAssign.

Homework #1

Due Jan. 19, 5PM

Assignment :
This assignment is on WebAssign

Homework #2

Due Jan. 26, 5PM

Assignment :
This assignment is on WebAssign

Homework #3

Due Feb. 6, 5PM

Assignment :
This assignment is on WebAssign

Homework #4

Due Feb. 11, 5PM

Assignment :
This assignment is on WebAssign

Homework #5

Due Mar. 5, 5PM

Assignment :
This assignment is on WebAssign

Homework #6

Due Mar. 6, 5PM

Assignment :
This assignment is on WebAssign

Homework #7

Due Mar. 20 5PM

Assignment :
This assignment is on WebAssign

Homework #8

Due Mar. 25 5PM

Assignment :
This assignment is on WebAssign

Homework #9

Due Apr. 10 5PM

Assignment :
This assignment is on WebAssign

Homework #10

Due Apr. 18 5PM

Assignment :
This assignment is on WebAssign

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Exams

We will have two midterms and one final exam

Midterm #1 Date: Thursday, Feb. 15

Midterm #2 Date: Tuesday, March 6

Midterm #3 Date: Thursday, April 19

Final Date: Thursday May 3rd

10AM - 12PM


You can find the Final Exam calendar here.

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Grading policy

Homework will count for 20% of your final grade, and the three midterms and final will count for 80%. 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%.

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