ST 744 - Spring 2005 - Syllabus
Categorical Data Analysis
ST 744 - Spring 2006 - Syllabus
Tuesday-Thursday, 10:15 - 11:30, 214 Daniels
Prerequisites: ST 512 and ST 522
Course Description
Statistical models and methods for data with categorical responses
including the analysis of contingency tables, logistic and
Poisson regression, and generalized linear models. Survey of
asymptotic and exact methods and their implementation using
standard statistical software.
Course Objectives
The students will be able to recognize important types of categorical
data and use appropriate methodology and computer software to make
valid inferences about the associated populations.
Instructor
Dennis D. Boos     212 Patterson Hall
email: boos@stat.ncsu.edu
phone: 515-1918
Office Hours: 10:00 - 11:30 a.m. Wednesday (but feel free to drop in when convenient)
Grader
Mingyan Huang    
320 Patterson
Office Hours: Wednesday, 1-2 pm -- 9 Patterson Hall.
Student Learning Objectives
By the end of the course, the student will be able to
- identify the main distributional structures: multinomial,
product multinomial, product binomial, multiple hypergeometric.
- identify important statistical models and their associated
notation: independence in an I by J table, conditional independence
in an I by J by K table, logistic regression model, Poisson regression
model, generalized linear model (GLM), baseline category model, proportional
odds model, generalized estimating equations model.
- identify appropriate null hypotheses in the above models.
- test appropriate null hypotheses in the above models with Wald,
likelihood ratio, and score statistics.
- apply appropriate computer programs to analyze the above models.
- interpret the output from sas programs to analyze the above models.
- decide which statistical procedure should be used in a given situation.
Text
Categorical Data Analysis , Alan Agresti (2002), 2nd Edition, Wiley
This is a classic text with a new edition. We will be following the
book fairly closely, covering Chapters 1-7 and portions of 10-12.
Grading
Plus/minus grading will be used.
The course grade will be based on homework assignments, exams, and class
participation.
The relative weight given to each of these components is
| Homework | 10% | |
| Mid-Term Exam | 45% | Tuesday, Feb. 28, 6-9 pm, 307 Mann |
| Final Exam | 45% | Tuesday, May 9, 8-11 am |
Class participation refers to willingness to ask and answer questions and to
participate in class exercises and discussions. It will be used to improve
borderline grades.
Details of the plus/minus grading system. If WA is the overall
weighted average,
then the final course grade will be at least as good (but could be higher)
as obtained from the following table:
-
| Range |
Grade |
| 99<
WA
< 100 |
A+ |
| 92 <
WA < 99 |
A |
| 90 <
WA < 92 |
A- |
| 88 <
WA < 90 |
B+ |
| 82 <
WA < 88 |
B |
| 80 <
WA < 82 |
B- |
| 78 <
WA < 80 |
C+ |
| 72 <
WA < 78 |
C |
| 70 <
WA < 72 |
C- |
| 68 <
WA < 70 |
D+ |
| 62 <
WA < 68 |
D |
| 60 <
WA < 62 |
D- |
| 0 <
WA < 60 |
F |
I might adjust the ranges
down a little at the end of the semester. Thus an 88 final
average could be an A if I adjust ranges.
Miscellaneous
- Students are expected to attend every class.
Class time will be devoted to help you learn the material
but not to cover every detail . Part of your responsibility is
to ask questions in class to help you and others understand the text
or handout material. Please read ahead and be prepared for class.
-
Homework will be assigned almost every week. It will be
due at the beginning of class. Late assignments (due by the next lecture
after the official due date) will be accepted, but only one late homework
will get full credit; the others will be
multiplied by .75.  
I encourage students to work in groups
on homework if they like, but no one should copy directly from someone
else's paper (either present or past students).
-
The exams will be in-class, closed book exams. You will be provided
with calculators and scratch paper. No cell phones or other electronic
devices should be in sight or used in any way.
-
Audit credit requires a score of at least 50% on the homework. In general
I think audits are a questionable use of student time.
- Academic Integrity:
It is the understanding and
expectation that a student's signature on any test or assignment means
that the student neither gave nor received unauthorized aid.
Consult the following website for further details on the code of student conduct:
http://www2.ncsu.edu/prr/student_services/student_conduct/POL445.00.1.htm
- I will regularly ask for feedback on how the class is going.
Please help me with your suggestions.
For students with disabilities:
Reasonable accommodations will be made for students with verifiable disabilities.
In order to take advantage of available accommodations, students must register
with Disability Services for Students at 1900 Student Health Center,
Campus Box 7509, 515-7653.
http://www.ncsu.edu/provost/offices/affirm_action/dss/
For more information on NC State's policy on working
with students with disabilities, please see the Academic Accommodations
for Students with Disabilities Regulation
http://www.ncsu.edu/policies/academic_affairs/courses_undergrad/REG02.20.1.php