SLN MW 10:20-11:35 pm in SCI 336

This is a 3 credit class. Consequently, we officially meet for 150 minutes every week. However, I will happily answer questions until 12:25 on Mondays or 12:05 on Wednesdays. Consider it a "built-in" office hours.

I've finished grading your final and calculuated your final grades, which are posted on the Catalyst Gradebook.

Some notes on my methods:

1.  Recall the percentages: HW 25%, Quizzes 10% each, Project 15%, Final 30%.
2. Homework was a boon to almost everyone--especially those that did the extra credit assignment at the end. I capped your homework percentage at 100%.
3. Most people benefitted from the "replace your lowest quiz score with your score on the final".
4. Challenge problems were used to determine which direction borderline cases should be moved in favor of. A strong performance on the final or lots of challenge problems gave you the benefit of the doubt. A weak performance on the final and no challenge problems went in the opposite direction (regardless of how close to borderline you were).

It has been my pleasure to teach you this quarter. Best of luck on your futures. I always like to follow student's progress--so feel free to stop by and chat even if you aren't taking another math class.

You have a written project in this class, due on the last day of the quarter (December 5).

We have a quiz coming up on Wednesday, November 5. It will cover sections 2.3-3.5

Good first day. Looking forward to Monday. In the mean time, please help select times for office hours that work best with your schedule by completing this survey (you should have gotten an e-mail announcing it on Thursday.)

"The equations central to the study of linear algebra are the linear systems Ax=b and the eigenvalue problem Ax=lx. It is simply amazing how much there is to say (and learn) about those two equations." 

This semester we will be finding out just how much there is to learn about these two equations. We will be tackling chapters 1-5 and 7 In David Poole's book Linear Algebra: A Modern Introduction. Topics: vectors; matrices and systems of linear equations; linear independence, span, basis, dimension, vector space; linear transformations; eigenvectors and eigenvalues; orthogonality.