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.
Choose Stat > DOE > Factorial > Create Factorial Design.
Under Type of Design, select General full factorial design.
From Number of factors, select 3.
Under Name, for Factor A, type Website, for Factor B, type Product, and for Factor C, type Message style.
Under Number of Levels, enter 3 for each factor. Click OK.
Under Type, select Text for each factor.
Under Level Values, for Website, name the levels News, Social Media, and Sports.
Under Level Values, for Product, name the levels Car, Video Game, and Medicine.
Under Level Values, for Message style, name the levels You know you should., Just the facts., and That is awesome!.
Select Summary table and design table.
Click OK in each dialog box.
Interpret the results
The first table gives a summary of the design: the total number of factors, runs, blocks, and replicates.
The design table shows the experimental conditions or settings for each of the factors for the design points using coded factor names and levels. For example, in the first run of the experiment, Factor A is at level 1. Factors B and C are at level 3. With 3 factors that each have 3 levels, the design has 27 runs. In the worksheet, Minitab displays the names of the factors and the names of the levels. Because the manager created a full factorial design, the manager can estimate all of the interactions among the factors.
Minitab randomizes the design by default, so when you create this design, the run order will not match the order in the example output.