Statistics 662: Environmental Statistics - Spring Quarter 2008
Instructor
Dr. Catherine Calder
| Office: 408A Cockins Hall |
Office Hours: TTh 10:30-11:30am |
| E-mail: calder@stat.osu.edu |
Office Phone #: 688-0004 |
Grader
Yonggang Yao
| Office: 304F Cockins Hall |
Office Hours: By Appointment |
| E-mail: yao@stat.osu.edu |
Office Phone #: 292-5375 |
Course Description
This course aims to provide an introduction to the types of statistical analyses used in environmental studies. Topics include sampling design, causality, limits of detection, toxicology, risk analysis, time series, spatial statistics, and hierarchical modeling. The course focuses on applications in a variety of different areas including ecology, environmental health, environmental monitoring, and remote sensing of the environment.
Prerequisites
Stat 530 or equivalent
Website http://www.stat.osu.edu/~calder/stat662-sp08/
Important announcements, lecture notes, homework problems and
solutions, computing references, and other information about the class
are posted on the course website.
Lectures TTh
9-10:18am in McPherson Chemical Lab
(MP) Room #2019
Lecture notes will be posted on the course website before
class. Please read the sections of the textbook that will be covered,
and print out a copy of the lecture notes before each class. There
may be parts of the notes that you should fill in during lecture, and
you may need to take separate notes on examples that are not in the
lecture notes. Unless instructed otherwise, you are responsible for
all of the material in the sections of the book that are covered in
lecture even if some of the material in the book section is not
covered in class. If you are unsure if you are responsible for a
particular topic, be sure to ask the instructor.
Required Textbook
Environmental Statistics: Methods and Applications (2004), by Vic Barnett
Article Presentation and Final Project
Each student is required to present a journal article on a topic in environmental statistics during the quarter and to complete a final project which will involve both an oral and written component. More information on these assignments will be distributed in class.
Homework
Assignments
There will be four homework assignments for the
course. You are encouraged to work together on the problems, but each
student must hand in his or her own work. DO NOT COPY any part
of another student's homework including computer output.
Solutions to the homework problems will be posted on the course
website. Late homework assignments will be accepted until the
solutions have been posted on the website. Once the solutions have
been posted, late homework will not be accepted. If you are unable to
come to class the day a homework assignment is due, please contact the
instructor. Re-grade requests on the homework problems must be
submitted in writing to the course grader within one week of the day
the solutions are posted.
Grading
The following is a breakdown of the final course grades:
| Final Project | 30% |
| Homework | 40% |
| Article Presentation | 20% |
| Class Participation | 10% |
Computing
We will be using the R statistical computing package, which is freely available. No prior knowledge of R is required, although some experience with R (or S-plus) will be helpful. R is available in the Department of Statistics computing laboratory, although this facility is only available to Statistics students. Links to the R website (where you can download R) and other computing resources are available on the course website. Most homework assignments will require some computing. Please cut and paste your computer output and graphs into your homework solutions.
Special
Accommodations
If you need any accommodations based on the
impact of a documented disability contact the instructor privately to
discuss your specific needs. You should also contact the Office of
Disability Services to coordinate special accommodations.
Academic
Misconduct
Academic misconduct will not be tolerated and
will be dealt with procedurally in accordance with university
policy.
