Course outline, policies, and syllabus

Main text: Chapter I | Chapter II | Chapter III | Chapter IV

Supplementary texts (not required): Linear Algebra and Its Applications (Strang); Elementary Linear Algebra with Applications (Anton and Rorres)

Lecture times: 11:00AM - 12:30PM TuTh in LSK 200

Instructor: Justin Tzou

Email: jtzou at math dot ubc dot ca

Office hours: By appointment - I am in everyday, but try to make your appointments on Tuesdays and Thursdays if possible. I will also usually be available right after class for quick questions.

Office location: My office is in a no-student area - the default meeting place will be in the seating area on the fourth floor of ESB by the elevator unless otherwise agreed upon. I will also usually be available right after class for quick questions.

Grading scheme

- assignments (approximately 6-8 over the term; late homework will not be accepted; worst one will be dropped): 25%
- midterm (Thursday Mar. 2 during class time in LSK 200): 25%
- final exam (date set by UBC): 50%

The midterm grade of those students who miss the midterm exam (with proper documentation given within 72 hours of the midterm) will be replaced by that obtained on the final exam. There will be no makeup exams given under any circumstances.

For the midterm and final exam: no calculators, no notes, no books, no cell phones or other electronic devices of any kind.

MATLAB/GNU Octave

To complete the work for this course, you will need access to MATLAB software. MATLAB is a widely used program for numerical computations with matrices. As a UBC student, you may obtain a free Student Version here -- this version will be sufficient for this course, and I strongly recommend you go with this option. You also can access MATLAB in the math department computer labs. These are located in LSK 121 and 310. The labs hours are posted here. You may use any free terminal in the labs during these times. You will need an account to use the terminals -- please let me know if you need access. If you prefer, you may also use GNU Octave, which is an open source MATLAB clone that is available for free. It is included in most Linux distributions. Windows and Mac versions are available for free download. However, I will probably only be able to answer questions regarding MATLAB.

Course plan

From the main text above, we will plan to cover approximately the following sections (time considerations will dictate what we are ultimately able to cover):

- Chapter I: everything except for I.2.4 and I.2.5
- Chapter II: all of II.1, all of II.2, II.3.1-7 (inclusive)
- Chapter III: all of III.1 except for III.1.5, all of III.2, all of III.3, (III.4 is not covered in the exam), III.5.1
- Chapter IV: all of IV.1 except for IV.1.10, IV.2.1-3
(inclusive), IV.2.5, all of IV.3, IV.4,
IV.6.1-2 (inclusive), IV.7.1-3 (inclusive)

Useful links

- past exams (some past exams may have MATLAB coding questions - that material will not be tested this term)
- partial solutions to past exam questions

Class notes

- 01/03/2017: (Ch.1) linear systems, vector norms, matrix norms | TYPO: on p.6, every 3/5 should be a -3/5; sorry! | MATLAB intro
- to run the MATLAB script, save it in a directory, open MATLAB, navigate to that directory, open the file, then run it by either pressing F5 or the 'run' icon
- alternatively, once in that directory, type jan_03_mat in the command window
- please let me know if you have issues with running the script
- the link to the MATLAB download is above

- 01/05/2017: (Ch.1) review, matrix norms | least squares fitting demo
- for the MATLAB code, please see p. 17 and p. 21 in the notes for the setup of the problem

- 01/10/2017: (Ch.1) matrix norms, condition number, Lagrange interpolation | proof of the first inequality on the bottom of p. 35 | map of circle by a random matrix: run file and function | other useful commands
- save these two files in the same directory; then run the run file, which is jan_10_mat.m
- notice
that the variables t, x_1, x_2 are created in the function computex(N),
but you do not have access to these variables once the function
exits
- 01/12/2017: (Ch.1) Lagrange interpolation, cubic spline interpolation | Lagrange interpolation demo
- for the code, please refer to notes on Lagrange interpolation
- take
a look at the output of the code - for the second example, the code
outputs the difference in the coefficients resulting from the small
change in one of the data points;the change is very large because of the large condition number of the Vandermonde matrix when there are many data points

Assignments

- this problem along with problems 1(b), 2, 4, 8, 13, 14, 16 from here | code for the umbrella problem | due Jan. 24 at the beginning of class