Design of Experiments (DOE) is the discipline concerned with the optimal acquisition and analysis of data for the purpose of investigating and controlling natural phenomena. Usually the investigator seeks to understand the effect of various factor combinations ("treatments") on some variable of interest. As a result, DOE is very useful in engineering, scientific, and management fields. Within engineering disciplines, DOE is useful for improving existing processes and designing new processes and products.
In this course we will cover DOE methods starting with single factor experiments and progressing to multifactor studies including various screening designs, e.g., full and fractional factorial experiments, and mixture designs. We will also discuss methods for experimentally optimizing processes and products, in particular, response surface methods.
The purpose of this webpage is to provide convenient access to various materials, such as the course syllabus, hw's, and supplemental materials, e.g., Minitab macros. If you have any questions, please e-mail me at email@example.com.
In order to optimize MA487 for current and future Rose students,
ongoing feedback beyond that provided by the course evaluations
is needed. Please provide suggestions/criticisms/comments via
the anonymous feedback link below: