In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors. Such an experiment allows the investigator to study the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable.

For the vast majority of factorial experiments, each factor has only two levels. For example, with two factors each taking two levels, a factorial experiment would have four treatment combinations in total, and is usually called a 2×2 factorial design.

As the number of combinations in a full factorial design can be too high to be logistically feasible, Smart Design uses Super-saturated design to investigate the effect of each factor on the response variable. To generate an optimal super-saturated design with respect to different criteria, you can choose from one of the four options available from the list that appears on clicking the button in the top left of this description.

For a detailed example of a two-level design industrial application, generation, interpretation and its utility for screening important factors, please refer to the Example and Multimedia Tab.