
SECONDARY Math 307101 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 307101 webpage.
Primary Page 
This webpage is a secondary webpage to the
home Math 307101 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: AD, Group 2: FK, Group 3: LQ, Group 4: RZ.
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 MF.
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
ugradinfo.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 45 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
help@ugrad.math.ubc.ca

Class Meetings 
We will meet 1:001:50pm, 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 50yearolds 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.

