For the latest version of JMP Help, visit JMP.com/help.


Design of Experiments Guide > Full Factorial Designs
Publication date: 11/29/2021

Full Factorial Designs

A full factorial design defines an experiment where trials are run at all possible combinations of factor settings. A full factorial design allows the estimation of all possible interactions. Full factorial designs are large compared to screening designs, and since high-level interactions are often not active, they can be inefficient. They are typically used when you have a small number of factors and levels and want information about all possible interactions. For example, full factorial designs often form the basis for a measurement systems analysis (MSA).

Figure 12.1 Full Factorial Design for Three Two-Level Factors 

Full Factorial Design for Three Two-Level Factors

Contents

Overview of Full Factorial Design

Example of a Full Factorial Design

Construct the Design
Analyze the Experimental Data

Build a Full Factorial Design

Responses
Factors
Select Output Options
Make Table

Full Factorial Design Options

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).