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Statistics 875
Categorical Data Analysis
Spring 2009
Instructor
Name: Christopher R. Bilder, Ph.D.
Office: Hardin Hall 342D (East Campus)
Office hours: MW 1:30-2:30PM, and by appointment
(for the 2nd and 4th Mondays of the
month, office hours end at 2PM due to departmental faculty
meetings)
Website: www.chrisbilder.com
E-mail:
STAT 875 website:
statistics.unl.edu/faculty/bilder/stat875 or
www.chrisbilder.com/stat875
Textbooks
Agresti, Alan (2007). An Introduction to Categorical Data Analysis. John
Wiley & Sons, Inc.: New York.
Supplementary:
Agresti, Alan (2002). Categorical Data Analysis. New York: John
Wiley & Sons, Inc.
Venables, W. N. and Smith, D. M. (2007). An Introduction to R. - Buy at
Amazon.com or use the PDF version which already comes in R (Select
HELP > MANUALS > AN INTRODUCTION TO R).
Prerequisites
STAT 801,
Statistical Methods in
Research
Strongly recommended: STAT 870,
Multiple Regression Analysis
Grades
Grades will be based upon the following:
| |
Percent of grade |
| Test #1 |
25% |
| Test #2 |
25% |
| Final exam |
20% |
| Projects, Quizzes, etc... |
30% |
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 90-92.5% and B+
is 87.5-90%.
You are required to turn in all projects electronically.
Projects need to be completed in Word documents and turned in before the
time they are due. 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.
I recommend completing the projects in groups. If you do work in a group, all
group members are expected to participate equally and have a complete
understanding of how to do all components of the projects. I reserve the right
to lower a student’s project grade if he/she does not abide by this group work
policy.
Statistical software
The statistical computer software package, R, will be used extensively to do
calculations in this class. R is available for free from www.r-project.org. The
specific link to download the Windows version is cran.r-project.org/bin/windows/base
and to obtain various add-on packages is
cran.r-project.org/web/packages.
This software is based on the syntax used in the award winning S language and is
very similar to the S-Plus statistical software package. All projects must be
completed using R unless otherwise announced.
Internet use during class
Do not access the Internet during class; this includes checking e-mail,
instant messaging, and browsing web pages. The only exceptions are if you are
asked by me to go to a specific web page during class.
Final Exam
The final exam is scheduled for 3:30PM
to 5:30PM on Wednesday, May 6.
How to be successful in the course
To be successful in this course, I strongly suggest that you should:
- Understand all the material in the course lecture notes
- Understand all R code and calculations (I expect you to rerun all of my code)
- 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.
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