STAT 464/664
Discrete Data Analysis
Fall 2005

Credits: 3 Prerequisite: STAT 367

Instructor:  Jeff Terpstra, 201H Waldron Hall
phone: 231-8188, email: Jeff.Terpstra@ndsu.edu
web page: http://www.ndsu.nodak.edu/instruct/terpstra/
Office Hours:  To be announced (TBA).
Class Meetings:  8:00 a.m. - 9:15 a.m., TR, LFGRD 102
Text:  An Introduction to Categorical Data Analysis by Alan Agresti
Course Description: Application of the binomial, multinomial, hypergeometric, and Poisson distributions to discrete data analysis.  Specific topics include contingency table analysis, logistic and Poisson regression, log-linear models, multicategory logit models, and ordinal regression.
Course Objective: To provide students with a basic understanding of fundamental categorical data analysis techniques.  Upon completion of the course students will ba able to apply these techniques to real world problems.
Homework:  Homework problems from the text book, and possibly other sources, will be assigned, collected, and graded periodically throughout the semester.
Exams:  There will be two exams (a midterm and final) during the semester.  You will be allowed one 8.5 x 11 inch sheet of paper with anything you wish to put on it for each exam.
Final Exam:  The final exam is exam #2 and will be given on Wednesday, December 14 from 10:30 a.m. - 12:30 p.m.  This exam is not comprehensive.
Make-up Policy:  Pre/Post-due-date coursework (i.e. homework and tests) will be allowed at the discretion of the instructor assuming the student provides the instructor with a legitimate excuse.  Pre-due-date coursework will be graded "as is" with no penalty.  However, the following grade will be given for all types of post-due-date coursework: 
post-due-date-grade = minimum{your score, class median}.
Grading Policy:  Homework - 50%, Exam#1 - 25%, Exam#2 - 25%
Grading Scale:  The following scale is guaranteed.
A [90, 100], B [80, 90), C [70, 80), D [60, 70), F [ 0, 60)
Special Needs:  Any student with disabilities or other special needs, who needs special accommodations in this course, is invited to share these concerns or requests with the instructor as soon as possible.
Academic Honesty Statement: All work in this course must be completed in a manner consistent with NDSU University Senate Policy, section 335: Code of Academic Responsibility and Conduct http://www.ndsu.nodak.edu/policy/335.htm.
Attendance:  Attendance is strongly recommended. Although not required, it might be used as one of the factors that influence a final grade for "borderline" cases. Also, at times, the material presented in class may vary from that presented in the text. Thus, class attendance and class notes are very important.
Incompletes:  University and Departmental policy will be followed on incomplete grades.
Provision: The instructor reserves the right to make changes to this syllabus at any time during the semester.