Description

This Master Prompt focuses on the screening stage of Design of Experiments, where researchers must reduce a potentially large candidate-factor set to a smaller, evidence-supported subset before detailed modeling, optimization, scale-up, or validation. It treats screening as a distinct inferential task rather than as a simplified optimization exercise. Researchers are guided to define the screening objective, establish scientifically defensible low and high factor levels, select an appropriate screening design, construct and execute the design matrix, estimate effects, evaluate statistical and practical importance, inspect aliasing and confounding, assess uncertainty, prioritize factors, and decide which variables should advance to subsequent experimental stages.