Homework: The homework that you turn in will be graded. It is your responsibility to work through as many problems as required for you to master the material.
Exams
The exams will be closed book and no calculators or other electronic devices
are permitted.
Exam I: Wednesday, October 1, in class.
The exam will cover the material in Chapters 1 and 2, including
homework and examples from lecture.
Exam II: Wednesday, November 12. The exam will cover the material in
Ch. 3-Ch. 5.
The Final Exam is cumulative. For Section 01 (Sujeet's Lecture) the Final is
Saturday, December 13 at 1:30 pm - 4:00 pm in ECCR 1B51. For Section 02 (Ann's Lecture)
the Final is Monday, December 15 at 4:30 pm - 7:00 pm in ECCR 151.
.
Here are some exams
from previous semesters. Please note that not all of the first exams
correspond to first exam material for our class. In other semesters,
different texts may have been used and the material may have been covered
at a different pace.
Resources
Matlab Examples
GaussElim.m, a simple program to do
Gaussian Elimination on a regular matrix
PGaussElim.m, Gaussian Elimination with permutation
for a nonsingular matrix.
Face Data is data you can use to try out the solftware below.
Principal Components is code you can use to calculate the principal components of 2D data. Try it on the data given above.
Gaussian and
Confidence are routines that calculate the confidence in a measurement, relative to given data.
Eigshow is a Matlab demo of the key idea behind the SVD.
This gives more information about the SVD, including applications.
A few years ago, some people (D. Bundy, E. Gibney, J. McColl,
M. Mohlenkamp, K. Sandberg, B. Silverstein, P. Staab, and M. Tearle)
in Applied Math developed a method to gently teach mathematical
writing. Martin Mohlenkamp maintains the
Good Problems site that this effort produced. This is an excellent
site for guidelines on how to write mathematics well.