Experimental Design and Analysis

3 credits · Undergraduate Programs

Introduction to statistical Design of Experiments (DOE) techniques for efficient data collection, analysis and interpretation. Hypothesis testing, Analysis of Variance (ANOVA), including blocking and nesting, in both full and fractional factorial designs to identify and control sources of variability. Applications of these techniques to optimize product and process performance through data-driven experimentation. Prerequisite(s): Digital Engineering 319 or Engineering 319. Antirequisite(s): Credit for Manufacturing Engineering 517 and 609 will not be allowed.