Home  > Syllabus

STAT 873
Applied Multivariate Statistics
Fall 2005


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
Web portal: www.chrisbilder.com
STAT 873 website: www.chrisbilder.com/stat873


Johnson, Dallas E. (1998).  Applied Multivariate Methods for Data Analysts.  Duxbury Press: New York.  

Click here to download Johnson's list of book errors. 

Supplementary: Wichern, D. W. and Johnson, R. A. (2002).  Applied Multivariate Statistical Analysis (5th edition).


STAT 801: Statistical Methods in Research

Recommended courses Regression models, ANOVA models, and matrix algebra


Grades will be based upon the following:  

  Percent of grade
1 Comprehensive Final   20%
2 Tests 40%
Projects, Quizzes, etc...   40%

Grading Scale:

A 90% and 100%
B 80% and <90%
C 70% and <80%
D 60% and <70%
F <60%

+ and letter grades are 2.5% from the above cut off points. For example, A- is 90 and <92.5% and B+ is 87.5 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:

bulletTake all exams
bulletComplete all projects
bulletUnderstand all the material in the course lecture notes
bulletUnderstand how to do all SAS and R code and calculations discussed during class
bulletComplete all homework
bulletRead 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.




Home ] Chat Room ] Data Sets ] Grades ] Homework ] R ] Links ] Message Board ] Projects ] SAS ] Schedule ] [ Syllabus ] Tests ] Word ]

  2003-5 Christopher R. Bilder