Statistics 8320
Lecturer:
Office:
Office hours:
Web site:
Class times:
Recommended
texts:
Prerequisite:
Winter 2007
Data Analysis II
Dr. Christine Spinka
SpinkaC@Missouri.edu
E-mail:
307D Middlebush Hall
882-2179
Phone:
Monday 1:15-2:15, Wednesday 2:00-3:00, or by appointment.
http://www.stat.missouri.edu/~spinkac/
Monday, Wednesday, and Friday, 9:00 – 9:50, in Middlebush 10.
Applied Multivariate Analysis, by Timm and Contemporary Statistical
Models for the Plant and Soil Sciences, by Schabenberger and Pierce.
STAT 8310, or instructor’s consent.
Evaluation:
Category
Exams given during the semester:
 Fri., Feb. 23rd; and
 Wed., Apr. 4th.
Comprehensive Final Exam:
 Fri., May 11th, 10:30 a.m. – 12:30 p.m.
Homework Problems
TOTAL
No. of items
2
Points each
100 points
Total value
200 points
1
100 points
100 points
100 points
400 points
Exams: There will be two in-class exams and one comprehensive final exam given in the
course. You will be permitted to use a formula sheet (8.5”x11”, one side only) and a calculator
on exams. (You are not allowed to use your notes, textbook, or other materials.) All exams must
be taken at the scheduled times. Exams may only be taken early or made-up in the event of a
pre-approved absence. If you miss an exam without prior approval you may be given a grade
of zero. If you must miss an exam for an approved reason, please see me as soon as possible to
make arrangements. (All “approved reasons” for missing an exam require that documentation be
presented in advance. For example, if you miss an exam for a medical reason, a note from a
physician is required.)
Homework: During most weeks of the semester, one or more homework problems will
be assigned. These problems are an important part of the learning process and will focus on the
material which I feel is significant. Problems will generally be assigned over material which we
have completed and should be viewed as an opportunity to solidify your understanding. Thus,
you may discuss the problems with your classmates, but please prepare your solutions
independently. Feel free to discuss any problems with me either in office hours or by email.
Because of the importance of homework, it will be worth one quarter of your final grade.
Syllabus/1
Material: I plan to cover multivariate analysis, nonlinear regression, generalized linear
models, linear mixed models and generalized linear mixed models. The multivariate material
can be found in the Timm text, while the other topics can be found in Schabenberger and Pierce.
Some material will be presented in lecture that is not covered in the book, and much of the
material in the text will not be discussed in lecture. You are responsible for the content of all
lectures and all assigned reading.
Software: You will be using the SAS software package to perform data analysis in this
class. The software is available in many of the computer labs on campus. Your textbook will
provide a good reference to get you started using SAS. Additionally, SAS help is available in
Middlebush in the evenings.
Academic honesty: Academic honesty is fundamental to the activities and principles of a
university. All members of the academic community must be confident that each person's work
has been responsibly and honorably acquired, developed, and presented. Any effort to gain an
advantage not given to all students is dishonest whether or not the effort is successful. The
academic community regards academic dishonesty as an extremely serious matter, with serious
consequences that range from probation to expulsion. When in doubt about plagiarism,
paraphrasing, quoting, or collaboration, consult the course instructor. If it is determined that a
student has cheated, he or she will be given zero points on the assignment in question and be
turned in to the Provost for disciplinary action. In addition, by committing an act of academic
dishonesty, a student places doubt on the legitimacy of all work completed in the course beyond
the act of academic dishonesty. As a result, a student who commits an act of academic
dishonesty may be given a failing grade in the course regardless of his or her performance
beyond the act of academic dishonesty.
Academic accommodations: If you need accommodations because of a disability, if you
have emergency medical information, or if you need special arrangements in case the building
must be evacuated, please inform me as soon as possible (privately, either after class or during
office hours). To request academic accommodations (for example, a notetaker), students must
register with Disability Services (AO38 Brady Commons, 882-4696). Disability Services is the
campus office responsible for reviewing documentation provided by students requesting
academic accommodations, and for planning accommodations in cooperation with students and
their instructors, as needed and consistent with course requirements. All academic
accommodations must be provided through disability services. If, for example, you are entitled
to additional time to take the exams you must take the exams at the Disability Services office.
Under no circumstances can your instructor allow you extra time (or other accommodations) in
the regular exam setting.
Syllabus/2