A full factorial design is a design in which researchers measure responses at all combinations of the factor levels. Minitab offers two types of full factorial designs: 2-level full factorial designs that contain only 2-level factors.

A marketing manager wants to study the influence that three categorical factors have on the ability of test subjects to recall an online advertisement. Because the experiment includes factors that have 3 levels, the manager uses a general full factorial design.

Minitab provides 2-level full and fractional factorial designs, 2-level split-plot designs, Plackett-Burman designs, and general full factorial designs with more than two levels. When choosing a design you need to:

Choose Stat > DOE > Factorial > Create Factorial Design. From Number of factors, select 6. Click Designs. Select the 1/4 fraction design. Click OK in each dialog box.

Use Create General Full Factorial Design to create a designed experiment to study factors that can have any number of levels. You can use a general full factorial design to create full resolution, 2-level designs for 8 or more factors.

Choose Stat > DOE > Factorial > Create Factorial Design. In Type of Design, select 2-level factorial (specify generators). From Number of factors, select 5. Click Designs. Select the Full factorial design. Click Generators. In Add factors to the base design by listing their generators (e.g. F=ABC), enter F = ABCD G = ABCE H = ABDE J = CDE ...

Use Create 2-Level Factorial Design (Default Generators) to create a designed experiment to study the effects of 2 − 15 factors. With a 2-level factorial design, you can identify important factors to focus on with further experimentation.

To specify the design, select the design resolution, the number of center points, replicates, and blocks. You can use Power and Sample Size for 2-Level Factorial Design to help you to determine an appropriate number of center points and replicates.

A design with 2 replicates and 18 experimental runs has a power greater than 90%, which meets the team's requirements. The power curve shows the relationship between power and the size of the maximum difference.

Stat > DOE > Factorial > Create Factorial Design > Designs To specify the design, enter the factors and replicates. You can use Power and Sample Size for General Full Factorial Design to help you to determine an appropriate number of replicates.