SECONDARY Math 307-101 DETAILED PAGE, Fall 2013

This is a second course in linear algebra, whose goal is to introduce numerous applications and some practical aspects of linear algebra. We assume that you have taken one semester of linear algebra (e.g., Math 152, 221, or 223).

There is no textbook for the course. Instead, we will use this set of notes, which is still under development (i.e., we expect some revisions and new material during the semester).

We will not spend time much time reviewing algorithms you learned from your previous course in linear algebra. To help you review these algorithms, we will refer to the text 3,000 Solved Problems in Linear Algebra by Seymour Litschutz; alternatively, you can use your previous text(s) to review these algorithms, but I will refer only to the aforementioned text.

In particular, the course is organized around applications, and will cover some of the following: Card shuffling, PageRank, power method, interpolation, least squares, graphs and networks, recursively defined functions, Markov chains, principal coordinate analysis, JPEG compression, finite difference approximations, FFT, Fourier analysis, Anderson tight binding model. The topic of Markov chains is really many topics in one, as it includes many models such as PageRank, card shuffling, and others.

The midterm will take place during class time on Friday, October 25. Location TBA.

This webpage is a secondary webpage to the home Math 307-101 webpage.

Primary Page This webpage is a secondary webpage to the home Math 307-101 webpage.
Midterm The midterm will take place during class time on Friday, October 25. Location to be announced.
Notes and Materials The main text is the following set of notes; the text's appendix will give a blog, used to give some additional class notes and to indicate roughly which topics were covered when. Any additional materials used in class will be posted here. We will use some free material from Experiements with MATLAB, by Cleve Moler, and his exm toolbox.
Review Basic linear algebra algorithms will not be discussed at length. I will to 3,000 Solved Problems in Linear Algebra by Litschutz to review this material, and this book gives solutions for all its questions. If you are comfortable with linear algebra, the textbook you used for Math 152, 221, or 223 should suffice, but it may not give you the worked out solutions.
Office Hours Office hours will be given by appointment (scheduling via email to jf at math dot ubc etc. usually works best) When things get too busy, I will give office hours by fixed hours which I will post (this will always happen just before an exam).
Matlab Matlab is the dominant industry standard for most of numerical linear algebra; many linear algebra packages are written only in Matlab. The student version at the UBC Bookstore costs $120 and is the version that I will use in this course (i.e., this version is good enough); this version runs on Windows/Mac/Linux. Homework will involve some computations; at times I may supply some sample code in Matlab. You will be given computer accounts with access to Matlab, but you may have to physically show up in the lab at certain hours; LSK121 and LSK310 have Matlab 2009a installed. For documentation on Matlab, you might try: MATLAB documentation page
Matlab Demos In Class At times I will give a brief demo of a Matlab computation. This will usually require a few minutes of setup. Hence, for practical purposes, I will almost always set this up before class and give the demo at the start of class.
Alternatives to Matlab At your own risk, you may use any alternative language to Matlab to do your computations. I do not guarantee that any alternative to Matlab will work for all the problems, but in practice the following languages should be able to all or almost all of the homework problems as easily as Matlab, provided you know the language reasonably well: Maple (used in Math 210), Octave (GNU product modelled on Matlab, but not exactly the same...), Mathematica, certain packages in Fortran, in C, etc.

Note that, for example, if you give Matlab the expression [ 1, 1; 0, 1]^100, Matlab returns the answer scientific notation; but the equivalent expression in Maple will return the exact answer, unless you force scientific notation by "evalf" (or something like that...). If you elect to use Maple, you are responsible for knowing to invoke "evalf" appropriately.
Grade You will be graded on the basis of a final (f), one midterm (m), and homework (h). Your grade will be computed as:
.10 max(h,m,f) + .30 max(m,f) + .60 f
Hence if you get 100% on the final and 0% on everything else, you get a 100% for the course; however, I have yet to see this happen... Ever...
Homework Homework will be assigned roughly weekly. Please write the first three letters of your last name in large, clear, block letters at the top the first page, and staple your homework. Please hand your homework by alphabetical order your last name, to make it faster for the TA to enter in the grades into a spreadsheet: Group 1: A-D, Group 2: F-K, Group 3: L-Q, Group 4: R-Z. Your grade for each homework is calculated as follows:
50% F + 50% (A/6)
where F is the fraction of problems that you have taken a reasonable first step towards a solution (in the opinion of the TA), and A is a more careful assessment of three problems which I shall indicate in advance (with an [A] in front of the problems); each of the three assessed problems will be marked 0, 1, or 2, for a total of a possible 6 points. In addition, the TA will comment on the rest of the problems as time permits (but this has no bearing on your homework score). This system is designed to be fair, and yet leave the TA with a maximum amount of time to devote to writing additional solutions to the sample exam problems (currently under development). Please print clearly in dark ink or pencil on your problem sets; I have instructed the TA to spend roughly an equal amount of time on each homework solution, and not to bother with homeworks that are too difficult to decipher.

Your overall homework grade is the average of the top half of your homework scores.

Homework #1, due Monday, September 16. Solutions to Problem 1, Problem 2, Problem 3, Problem 4, Problem 5, Problem 6.
Exam Questions, Learning Objectives From time to time I will present "learing objectives" for material we cover; this will mostly consist of a (fairly long) set of sample exam questions. I will provide solutions to some of these questions, but not to all of them. Some of these sample questions will appear on the homework, perhaps implicitly in a Matlab computation.
Undergrad Labs Lab hours: 8:00am - 5:00pm M-F. Alarms from 6:00pm - 8:00am. Labs will be closed/alarmed on weekends and holidays. You may use the lab during lab hours except when another class has a scheduled lab hour; see the math ugrad lab schedule. The ugrad-info.txt file explains how to get your account name and passwords, and has some other information.
You can print out your Matlab to a limit of 35 pages per course. This is roughly 4-5 pages per homework; please let me know if this is a problem. See under "Computer Lab Facilities" (or do a "find" for 35) in this program description booklet, or here, where you will learn that you can pay $20 per 100 additional pages (you could think of it as a donation to a worthy cause).
If there are any problems with labs, you can send email to
Class Meetings We will meet 1:00-1:50pm, MWF, Buch B215; first class Wed., Sept. 4, last class Fri., Nov. 29. Class will not be held on September 18, during the West Coast National Event of the Truth and Reconciliation Committee (during which you are encouraged to participate) which is free and will take place at the PNE (where the 50-year-olds go to hear Heart and REO Speedwagon for a $12 entry fee), see TRC FAQ for more info; the university is closed on October 14, Thanksgiving, and November 11, Remembrance Day.
Other News No news is good news.
Classes start: Wednesday, September 4, end November 29.

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