| |
STAT 873
Applied Multivariate Statistics
Fall 2005
Instructor
Name: Christopher R. Bilder, Ph.D.
Office: Hardin Center 342D (East Campus)
Office hours: MW 10-11AM, M 3:30-4:15PM (Avery 250), and by appointment
E-mail:
Web portal: www.chrisbilder.com
STAT 873 website:
www.chrisbilder.com/stat873
Textbooks
Johnson, Dallas E. (1998). Applied Multivariate Methods for Data Analysts. Duxbury Press: New York.
Click here
to download Johnson's list of book errors.
Prerequisites
STAT 801: Statistical Methods in Research
Recommended courses – Regression models, ANOVA models, and matrix algebra
Grades
Grades will be based upon the following:
| |
Percent of grade |
| 1 Comprehensive Final
|
20% |
| 2 Tests |
40% |
| Projects, Quizzes, etc...
|
40% |
Grading
Scale:
| A |
³90%
and £100%
|
| B |
³80%
and <90%
|
| C |
³70%
and <80%
|
| D |
³60%
and <70% |
| F |
<60%
|
+ and – letter grades are 2.5%
from the above cut off points. For example, A- is
³90
and <92.5% and B+ is
³87.5
and <90%.
A project completed in an
unreadable or unprofessional manner will be returned to the student.
The project may be redone and turned in again; however, points will be
deducted from the grade. No late
projects, quizzes, etc. will be accepted.
You are required to turn in all projects
electronically. E-mail projects to me in Word documents BEFORE the time
the project is due. I will e-mail you an acknowledgement if it has been
received. If you do not receive an e-mail acknowledgement from me, it is
your responsibility to determine what happened to the project.
Computer usage
The statistical software packages, SAS
and R, will be used extensively to do calculations in this class. Personal
copies of SAS may be obtained for a fee from the Department of Statistics. R is
freeware and may be obtained from the R project website at
http://www.r-project.org. In
particular, the latest windows version of R can be downloaded from
http://cran.r-project.org/bin/windows/base and is located in the file
rw2011.exe. All projects must be completed using SAS and R unless otherwise announced.
Projects completed using other software packages will not be accepted.
Final Exam
The final exam is scheduled for 7:30-9:30AM
on Friday, December 16.
How
to be successful in this course
To
be successful in this course, I strongly suggest that you should:
 | Take all exams |
| Complete all projects |
| Understand all the material in the course lecture notes |
| Understand how to do all SAS and R code and calculations discussed
during class |
| Complete all homework |
| Read the corresponding sections of the textbook as we cover
the course material |
|
If
you have problems with completing any of the above, please ask questions in
class or stop by during my office hours.
|
|
