AbstractIn many scientific investigations, interest lies in studying the effects of several input variables simultaneously on an output variable. Factorial experiments are ideally suited for such investigations. The importance of factorial experiments stems from the fact that such experiments allow the estimation of individual effects of the input variables as also their inter‐dependence at the same time, thus providing a basis for drawing inference over a wide range of conditions. Some basic ideas of factorial experiments and issues related to the designing of such experiments are discussed with emphasis on symmetric 2‐ and 3‐level experiments. WIREs Comp Stat 2011 3 577–581 DOI: 10.1002/wics.191This article is categorized under: Statistical Models > Classification Models