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Winter Quarter 2017

Webcast of the lectures

Just before lecture, about 1:30pm PST on Tues and Thurs, we'll post the link to the webcast of the lecture.

Instructors

Eli Holmes, eeholmes (at) uw [dot] edu, faculty.washington.edu/eeholmes/

Eric Ward, warde (at) uw [dot] edu, faculty.washington.edu/warde/

Mark Scheuerell, scheuerl (at) uw [dot] edu, faculty.washington.edu/scheuerl/

Lectures

Tuesday & Thursday from 1:30-2:50 in FSH 203

Computer Lab

Thursday from 3:00-3:50 in FSH 207

Grading

Your grade for the course will come from 4 elements:

  • Homework (30%)

  • Final paper/project (40%)

  • Peer reviews (20%)

  • Class participation (10%)

Homework will be assigned each Thursday and is due by 5:00 PM PST on the following Tuesday. It will consist of some short answers and R code based on topics in lab. There will be 6 assignments worth 5% each.

Each student will have to write a complete, publishable (<20 page) paper that may, or may not, serve as a component of their thesis/dissertation. Given that some students might not have their own data, these papers can be done alone, or in pairs (expectations will be higher for joint work). Students may also use data from the instructors, or datasets included in R libraries. The paper is due by 11:59 PM PST on March 10.

Each student will also have to provide 2 anonymous peer-reviews of their colleagues’ papers (10% each), which are due by 11:59 PM PST on March 16.

This is a graduate-level course and we expect a certain amount of engagement from each student, which includes attending lectures and computer labs.

Conduct

We expect everyone to abide by the UW Student Code of Conduct. If you believe you have been a victim of an alleged violation of the Student Conduct Code or you are aware of an alleged violation of the Student Conduct Code, you have the right to report that to the University (contact info here).

Important Deadlines

  • Jan 27: Identify data for the final project and submit an abstract outlining the problem and research question(s)

  • Feb 10: Discuss your proposed methods with at least one of the instructors

  • Mar 10: Final project/paper due

  • Mar 16: Peer reviews due

Announcements

No announcements

Send questions about this workspace to Eli Holmes.