Full Factorial Design within experimental design (DoE) is a systematic statistical methodology for evaluating the effects and interaction terms of multiple input variables on one or more response variables by testing all possible combinations of factor levels simultaneously. This approach relies on orthogonal arrangements where each experiment constitutes a unique combination of factors, allowing for the efficient estimation of main effects without confounding them with interactions in balanced designs. The theoretical foundation involves determining the sample size required to distinguish significant differences from noise via variance analysis while adhering to the principle that computational or physical effort scales exponentially ($2^K$) with the number of factors $K$.
Full Factorial Design within experimental design (DoE) is a systematic statistical methodology for evaluating the effects and interaction terms of multiple input variables on one or more response var…