Course Description
Methods for constructing and analyzing designed experiments are considered. Concepts of experimental unit, randomization, blocking, replication, and orthogonal contrasts are introduced. Designs include completely randomized design, randomized complete block design, Latin squares design, split-plot design, repeated measures design, and factorial and fractional factorial designs.
Athena Title
EXPER DESIGNS
Equivalent Courses
Not open to students with credit in STAT 6430
Prerequisite
STAT 6220 or STAT 4230/6230 or STAT 6320 or STAT 6420 or STAT 6315
Semester Course Offered
Offered fall, spring and summer
Grading System
A - F (Traditional)
Course Objectives
Students will learn basic concepts and methods for designing an experiment and analyzing data from the experiment. They will also learn strengths and weaknesses of these methods, enabling them to assess which method is preferable for a particular problem. They will obtain a thorough understanding of the basic concepts in design of experiments, including experimental and observational units, randomization, blocking and replication. Students will also learn how to deal with special treatment structures, including the factorial treatment structure. Inference methods for assessing differences among treatments or for specified comparisons of interest are discussed for each of the designs. In addition, students will learn how to select appropriate replication of treatments to meet objectives of the experiment. They will learn how to perform inferences based on the methods in this course by using a statistical software package.
Topical Outline
The topics covered in this course focus on different plans for collecting data in designed experiments and on the analysis of such data. The concepts of randomization, blocking and replication will be covered. Designs considered include completely randomized designs, randomized complete and incomplete block designs, Latin square designs and other row- column designs, and split-plot designs. Special treatment structures will be considered, such as comparisons to a control and factorial treatment structure. Construction of fractional factorials will also be considered. Analysis of variance, treatment contrasts, and sums of squares play important roles in the analyses. Both fixed and mixed effects models are considered.
Syllabus