Instructor:
Dr. Hongwei Long, office: SE 268, phone: 297-0810, e-mail: hlong@fau.edu
Course homepage: http://www.math.fau.edu/long/STA6446-SB07.htm
Time and Place:
MWF 3:30-5:40pm in SC 178.
Office Hours:
MWF1:00-2:30pm in SE 268.
Other times by appointment or just stop by the office.
Textbook:
Regression Analysis: Theory,
Methods, and Applications, by Ashish Sen and Muni Srivastava,
Springer-Verlag,
Course Description:
This course is designed to provide some basic theory, methods and applications of regression analysis. Topics covered include simple regression (least squares method), multiple regression, tests and confidence regions, indicator variables, the normality assumption, unequal variances, outliers and influential observations. The students are expected to gain a firm foundation in the theory of regression and the experience necessary to competently practice this valuable craft.
Prerequisites: STA 4442 or 4443.
Exams:
Take-home midterm |
Tentatively July 16-18. |
Final (or Project) |
Monday, August 6, 3:30-6:00 pm, location: SC 178. Closed book exam. The completed project can be submitted at any time before or on August 6. |
Assignments:
There will be about five 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: July 25, 2007
long