STA 4276F Evaluation (Fall, 2003)
The evaluation for STA 4276F (Fall, 2003)
will be as follows:

Attendance and class participation 50%.

Final paper 50%;
Participation Grade (50%):
Class Participation involves:
 attending class regularly and punctually;
 keeping up with the material as it is covered in class;
 answering questions posed by the instructor in class;
 posing your own questions about the class material;
 paying careful attention to the class lectures;
 assisting with the summary of the previous class.
Final paper (50%):
Each student who is taking STA 4276F for credit will be required to write
a final paper, due by 1:00 p.m. on Friday December 5 (no extensions!).
This paper shall involve reading several (related) research papers
about MCMC algorithms (which go beyond the material covered in
class), and:
 Summarising the content of the papers;
 Explaining the importance of the content for MCMC;
 Applying the content to some examples or cases not directly
discussed in the papers;
 Describing your applications clearly and in detail;
 Drawing whatever conclusions you can from your applications.
Your final paper should be at least 20 pages long (typed doublespaced),
likely longer.
To select the research papers for your final paper, you might
start by reading some papers from the MCMC Preprint Service (http://www.statslab.cam.ac.uk/~mcmc/)
and/or the Perfect MCMC Annotated Bibliography (http://dimacs.rutgers.edu/~dbwilson/exact/).
Once you have some idea of your topic, you should talk to me (some time
in October) to finalise your topic. All topics require my approval.
You should not choose the same topic as another student in the class.
However, if two students are interested in collaborating jointly on a
(more substantial) joint final paper, then that might be possible; talk
to me if you are interested in this.
Background:
Students unsure about their background in measure theory and Markov
chain theory should review a book about these subjects, e.g. Chapters 2,
3, 4, 8, and 15.2 of A First Look at Rigorous Probability Theory
(World Scientific, 2000, available at U of T Bookstore).
This document is available at http://probability.ca/jeff/courses/sta211103eval.html.