Lecture place and time: Tuesdays & Thursdays 11:30 - 12:50 in LOW 101

Course web site: http://www.stat.washington.edu/courses/stat538/winter12 Use it!

Instructor:	Marina Meila
	mmp@stat.washington.edu
Office hours:	Monday 2-3pm in PDL B-321 (TO BE CONFIRMED if there are no major conflicts)
Class mailing list:	stat538a_wi12@uw.edu
Textbooks:	Boyd & Van der Berghe -- required, Hastie ,Tibshirani & Friedman "Elements of Statistical Learning" -- recommended, Bertsekas and Numerical Recipes suggested. See the Resources page for links to on-line versions of these books. Occasionally I will hand out other reading materials in class or post them on the web.
Format:	The course will consist of two weekly lectures, a series of homework assignments and a final exam. Active class participation by questions, answers and comments is important and therefore it will be part of your grade.
Assignments:	Typically assignments will be posted on the web on Tuesdays and will be due the next Tuesday at the beginnining of class. The assignments will consist of (1) short programming assignments (typically, to implement a version or a special case of an algorithm presented in class) to be done in the programming language of your choice and (2) problems or other questions. The programming assignments will be split into two separate parts: output and results, which is the only part of the homework that is graded; this can be handed in on paper, or uploaded online through catalyst the code, which is submitted electronically, but never printed, and is typically not graded. Late homeworks will only be accepted in exceptional circumstances.
Teamwork:	Each class participant submits her/his homework individually. Unless explicitly allowed to do so, you are required to write your own code. However, discussing homework, on the class mailing list or elsewhere, is encouraged.
Grading:	(Approximately!) 10% class participation 65% assignments and 25% final exam.
Prerequisites:	See the