Stat 498B: Environmental Statistics

This page was last updated Wednesday, 27-Feb-2008 07:35:52 PST.

Syllabus

Class meetings

The class meets Wednesdays and Fridays 10:30-11:50 in Sieg 229. .

Text

There is no text.

Course requirements

Students need the background of an introductory statistics course (such as STAT 220 or STAT 311). Some background in environmental sicences would be useful, but is not required. The course counts as a major elective for Statistics.

Outline of the course

Course style

We will be working through 4-5 cases. These will start with some general scientific background, and then give the participants a task to be solved in groups. Some cases have more than one task, which need to be solved sequentially. The solutions will require different formats, such as in class presentations, web pages, papers etc. Grading will be based on class participation, group participation, and quality of solutions.

First assignment (due by 9 am January 11)

Send me email describing your background, what statistics classes you have taken, and why you are interested in the class.

Cases

Case 1: The ASARCO copper smelter in Tacoma.
The continuation is here.
An R script for doing an analysis of variance with the smelter data is available.
Another R script for doing a residual analysis of the data is here,
Some references for this case.
Case 2: Port Townsend Paper Corporation.
Case 2, continued.
Case 3 Spatial prediction.
Lab using geoR
Part 2
Part 3
Part 4
Part 5
Part 6
Part 7
Case 3, continued.

Study groups

The class will be divided up into groups of 3-4 individuals with diverse backgrounds. The groups will work together the entire course. The projects will require group reports. At the end of the quarter, each individual will assess every group member's contribution (including their own) to the group product.

Detailed schedule

The day-by-day schedule is being updated regularly and constitutes my best guess of what we will be doing on each day.

Online discussion

Online discussion can take place here. Feel free to add any comments you have.

Computing

R on the Web:

http://www.r-project.org/

http://www.stat.washington.edu/software/statsoft/R/

Chris Green's R primer.

Bookmarks

I maintain a set of bookmarks with references to Web pages relating to environment and statistics. For extra credit students can provide useful links not already among these bookmarks.

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