Design and Analysis of Industrial Experiments

Catalog description

Credits 3. 3 Lecture Hours. Fundamental theory, concepts and procedures required for industrial experimental design, statistical data analysis, and model building, with emphasis on engineering formulations and applications; one-factor experiments with and without restrictions on randomization, treatment comparison procedures, Latin and other squares, factorial experiments, full and fractional two-level factorial experiments, blocking in factorial designs, response surface methodologies and introduction to Taguchi methods. Prerequisite: STAT 212 or STAT 601 .