MATHS 429: Analysis of Variance in
Experimental Design Models (3)
Syllabus
1. Prerequisite: MATHS 321 or equivalent.
2. Course Description: Multivariate normal distribution; quadratic
forms; linear models; simple random, randomized block, Latin squares,
factorial, split-plot, balanced incomplete block design; analysis of
covariance; confounding; multiple comparison tests.
3. Course Objectives: Experimentation is a key component in
research. In the initial phases of
developing a research program, the various aspects of experimental design
should be incorporated. The initial research proposal should address such
issues as: which experimental setup to use, which factors to study, the manner
of obtaining the observations, and so on.
Aspects of experimental analysis are used in preparing final reports of
the work, and in the dissemination of the research results. Extracting relevant
information from the data, constructing valid estimates, and verifying the
existence of meaningful differences are some of these aspects. This course considers both the design and
analysis phases of experimentation.
4. Course Rationale: The role of a statistician in an experimental
program is not merely to analyze the results of the experiment, but also to
help the scientist plan his experiment in such a way as to produce valid
results as efficiently as possible. This
course would prepare a student for such a challenge. The course is a required course for students
majoring in statistics and is also an excellent course
for students who are in mathematics, business, psychology, and a host of other
areas where statistical methods are employed.
5. Course Content: Multivariate normal
distribution. Quadratic forms. Linear
models. Designs: simple random, randomized block, Latin squares,
factorial, split plot, balanced incomplete block. Analysis of
covariance. Confounding. Multiple
comparison tests.
6. Course Format:
The class will be taught through a lecture/discussion format. Students
will be expected to participate in class regularly, to study the appropriate
material, and to complete a variety of assignments using statistical software.
7. Evaluation of Student Performance: Course
grades are determined primarily by student performance on tests, quizzes, and
projects, as well as possibly homework and class participation. The evaluation and weight of these various
components are at the discretion of the individual instructor.
8. Evaluation of the Course: The instruction of the course is evaluated by
departmental student evaluations and peer evaluations. The course is reviewed and revised
periodically by the Department Undergraduate Programs Committee.
[VDM 10/2005]