Instructor
Dr. Catherine Calder
| Office: 408A Cockins Hall |
Office Hours: MW 10-11am |
| E-mail: calder@stat.osu.edu |
Office Phone #: 688-0004 |
Graders
Mr. Yoonsuh Jung
Mr. Yongku Kim
| Office: 305D Cockins Hall |
Office Hours: TTh 10:30-11:30am |
| E-mail: kim@stat.osu.edu |
|
Course
Description
Statistics 656 is an introductory multivariate
statistical analysis course designed for graduate students in the
Department of Statistics. The aim of the course is to introduce a
variety of standard statistical methods used to analyze multivariate
data, emphasizing the implementation and interpretations of these
methods. Topics covered include matrix computation of summary
statistics, graphical techniques, the geometry of sample data, the
multivariate normal distribution, principal components analysis,
factor analysis, canonical correlation analysis,
classification/discrimination, as well as cluster analysis if time
permits. We will use the R statistical computing environment and the
GGobi data visualization system; no previous experience using these
software packages is required.
Prerequisites
Statistics 645
(Applied Regression Analysis) or equivalent, knowledge of linear
algebra, and some experience with statistical computing packages are
required.
Website http://www.stat.osu.edu/~calder/stat656-sp07/
Important announcements, lecture notes, homework problems and
solutions, computing references, and other information about the class
are posted on the course website.
Textbook
Applied Multivariate Statistical Analysis,
Fifth Edition.
by Richard A. Johnson and Dean W. Wichern (required)
Lectures MW
8:30-9:48am in 0012 Arps Hall
(AP)
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
will be parts of the notes that you will need to fill in during the
lectures, 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 assigned even if some of the material in the book sections is not
covered in class. If you are unsure if you are responsible for a
particular topic, be sure to ask the instructor.
Computing
We
will be using the freely available R statistical computing
environment. R is available in the Department of Statistics computing
laboratory (note that this facility is only available to Statistics
students). Links to websites where R, as well as other reference
materials, can be downloaded 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.
In addition to using R for the homework problems, you will be expected
to be able to interpret R output on the exams. The GGobi data
visualization system will be demonstrated in class, but you will NOT
be asked to do any analyses using it outside of class.
Homework
Assignments
Six homework assignments will be given thought the
quarter. 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.
Exams
There
will be an in-class midterm given (tentatively) on Wednesday, April
25th. The date may change and will be officially announced on the
course website and in class. Re-grade requests on the midterms must
be submitted to the grader in writing within one week of the day the
midterms are handed back. A final take-home exam must be turned in no
later than Wednesday, June 6th at 12pm.
Grading
The following is a breakdown of the final course grade:
| Midterm | 35% |
| Final Take-Home Exam | 35% |
| Homework | 30% |
Grades on the exams may be curved if necessary.
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.
