ENVS 355: Special Topics in Environmental Studies
Environmental Data Analysis and Modeling
Instructor: Greg Bothun
Office hours MTRW 10 - noon. (but check the
Cameras First )
Office/Lab: 417 Willamette
email: nuts@bigmoo.uoregon.edu
Course Structure
This
course is designed to introduce Environmental Science students to the task efficiently representing data and to construct models
from that data and then to present that model in a convincing
fashion.
Virtually every environmental
problem is characterized by three things:
- Noisy/ambiguous data that defines the problem
problems are therefore usually defined by perception and opinion rather than
by objective data.
- Difficult physical modeling since not all of the input physics is known;
most environmental problems are intrinsically complex/chaotic
- Policy makers/public interest groups that do not understand science, the
scientific process and its limitations. In particular, there is wholesale
failure to understand the critical difference between Scientific
Plausibility and Scientific Provability .
This course is designed to immerse the students in these three intertwined
difficulties. Some of this will be done via assigned teams
that will carry out a data driven/modeling project and report
on the results via in class presentations. A very large goal of this class is to get the students to be facile at presenting data and arguments.
This class is being held in a wireless laptop classroom and we will be
making use of that infrastructure throughout the term. A by product of
this class is that you will learn how to use Microsoft Excel as a statistics
and data analysis tool.
There will be no assigned text book as there is certainly not one that
is relevant to this material.
Most all of the assignments in this class will be group based and will
take two weeks to do. A few individual assignments to build skills in key
statistics areas will also be given.
Lectures will be a mix of computer based presentations and standard
blackboard lectures and derivations. The derivations will make use of
some calculus in order to prove some things. In general, however, your
assignments will not require the use of Calculus.
The course web site will appear on Blackboard and will contain extensive
notes based on the topic of the day.
Course Grading will occur around the following guidelines:
There will be no midterm in this course but there will be a final exam.
The final exam will count for approximately 1/2 of your grade.
The remaining approximate 1/2 will come from various assignments,
some of which can be done collaboratively.
The goal in this class is to learn important techniques and to gain experience
building real models from real data. In this manner, I regard this class
as a skill building and proficiency based class and you will be graded
accordingly. In the past, no one in this class has received a grade lower
than B- .
Course Content
The content of this class will be highly fluid. Expect that.
This course has five main goals:
To familiarize students with some advanced statistical
concepts involving goodness of fit tests and overall data analysis
To get students to acquire data and understand
sparse sampling techniques and reliable tracers.
To use data to construct models with predictive
power and to assess their accuracy.
To get students to work together collaboratively
and to become facile at presenting their models and their assumption
set in terms of formulating a plan or strategy for dealing with
an environmental problem.
> To improve the electronic project reporting skills of the students. This is new but now seems important and necessary.
The course will begin with some tedious but necessary lectures on methodology and basic data analysis. Simple statistical procedures (linear regression, Z-test, probabilities) will be introduced during this time.
We will then move onto various environmentally relevant topics, such as
global warming, forest thinning, population projections, predator-prey
relation, energy generation problems, resource depletion issues, salmon
extinction, local climate change, etc. At this time its unclear which
exact topics we will emphasize. In any case group exercises
around these themes will be designed.
Environmental Data Analysis and Modeling
Instructor: Greg Bothun
Office hours MTRW 10 - noon. (but check the
Cameras First )
Office/Lab: 417 Willamette
email: nuts@bigmoo.uoregon.edu
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