# Specify the design for Create 2-Level Factorial Design (Specify Generators)

Stat > DOE > Factorial > Create Factorial Design > Designs

After you specify the base design, click Generators to specify generators for factors and blocks.

## Available designs

Select the number of runs and the design resolution for the base design. The number of runs in the design also depends on the number of center points, replicates and on whether you fold the design.

The resolution of the design depends on the generators that you use to add factors and blocks. For more information on resolution, go to What is the design resolution in a factorial design? For more information on choosing among the available designs, go to Choose a factorial design.

## Number of center points per block

If you want to include center points in your design, select the appropriate number of points. You can use center points to detect curvature in the response. You can also use center points to estimate variability without having to replicate all the corner points.

Center points are runs where numeric factors are set midway between their low and high levels. For example, if a numeric factor has levels 100 and 200, the center point is set at 150. If you have text factors, then Minitab adds a center point at each level of the text factor and the midway level of the numeric factors. For example, your design includes a text factor with the levels A and B and a numeric factor with the levels 100 and 200. If you add 1 center point to the base design, Minitab adds 1 center point at levels A and 150 and 1 center point at levels B and 150. Thus, Minitab adds 2 center points for each center point that you specify.

Replicates do not add additional center points beyond what you specify. For example, if you specify 3 center points, 2 replicates, and 1 block, then the design includes 3 center points.

## Number of replicates for corner points

Select the number of replicates for the corner points. Replicates are multiple experimental runs with the same factor settings (levels). One replicate is equivalent to the base design, where you conduct each run once. With two replicates, you perform each run twice (in random order), and so on.

Adding replicates can help increase the precision of your model and increase the power to detect effects. To determine how many replicates to include in your design, consider the available resources and the purpose of your design. For example, in a screening design or in sequential experimentation you could begin with the base design (1 replicate) and then consider whether to add replicates after you analyze the data. You can add replicates to your design later with Stat > DOE > Modify Design. For more information on replicates, go to Replicates and repeats in designed experiments.

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