Instructor:
Dr. Hongwei Long, office: SE 268, phone: 297-0810, e-mail: hlong@fau.edu
Course homepage: http://www.math.fau.edu/long/STA6446-S08.htm
Time and Place:
MWF 1:00-1:50pm in DP 101.
Office Hours:
MWF10:00-11:00am and 2:00-3:00pm in SE 268.
Other times by appointment or just stop by the office.
Textbook:
Introduction
to Time Series and Forecasting, 2^{nd} Edition, by Peter J. Brockwell and Richard A. Davis, Springer-Verlag,
Course Description:
This course gives a basic introduction to time series and forecasting methods which can be applied to finance, economics, engineering, and the natural and social sciences. Topics covered include stationary processes, ARMA models, spectral analysis, modeling and forecasting with ARMA processes, and non-stationary and seasonal time series models (the first six chapters of the textbook).
Course Objectives:
The students will be able to understand and master some basic time series and forecasting methods with applications to data analysis.
Prerequisites: STA 4442 or 4443 (Minimum Grade C).
Exams:
Midterm |
Friday, February 22, 1:00-1:50pm in class. Closed book exam. |
Final (or Project) |
Monday, April 28, 10:30-1:00 pm, location: DP 101. Closed book exam. The completed project can be submitted at any time before or on April 28. |
Assignments:
There will be about six homework assignments. These will involve using methods presented in class to solve problems from the textbook. Assignments should be handed in on the due date. Late assignments will not be accepted.
Grading:
Grading will be based on the following weighting:
30% Assignments
30% Midterm exam
40% Final exam (or Project)
There will be no make-up midterm. If a student has an acceptable excuse for missing the midterm, the weight of the midterm will be shifted to the final. Make-up final exam will be given only under exceptional circumstance, and written, verifiable excuses must be provided.
· Homework Assignments
Last modified: April 8, 2008
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