Design & Analysis of Experiments Startup Panel - Quick Tab

Select the Quick tab of the Design & Analysis of Experiments Startup Panel to access the design of experiments described here. Additional experiment types including Taguchi, Latin Square, and D- and A-Optimal designs are available on the Advanced tab. See also Experimental Design and Analysis - Index.

2**(K-p) standard designs (Box, Hunter & Hunter)

Select 2**(K-p) standard designs (Box, Hunter & Hunter) to generate or analyze standard fractional factorials and full factorials with two levels (and, optionally, center points), with or without blocking (see, for example, Box, Hunter, & Hunter, 1978, Montgomery, 1991). For a description of these designs, refer to the Introductory Overview.

3**(K-p) and Box-Behnken designs Select 3**(K-p) and Box-Behnken designs to generate and analyze designs with 3-level factors. Specifically, Statistica generates Box-Behnken designs as well as blocked 3(k-p) full and fractional factorial designs as enumerated by Connor and Zelen (see McLean and Anderson, 1984) for the National Bureau of Standards of the U.S. Department of Commerce. In the analysis, the main effects and interactions can be partitioned into linear and quadratic components. For a description of these designs, refer to the Introductory Overview.

Mixed 2 and 3 level designs

Select Mixed 2 and 3 level designs to generate and analyze designs with 2 and 3 level factors. Specifically, Statistica generates full and fractional factorial designs as enumerated by Connor and Young (see McLean and Anderson, 1984) for the National Bureau of Standards of the U.S. Department of Commerce. In the analysis, the main effects and interactions can be partitioned into linear and quadratic components. For a description of these designs, refer to the Introductory Overview.

Central composite, non-factorial, surface designs Select Central composite, non-factorial, surface designs to generate or analyze first- and second-order central composite (response surface) designs. For a description of these designs, refer to the Introductory Overview.

Mixture designs and triangular surfaces

Select Mixture designs and triangular surfaces to generate or analyze experiments for mixtures where the sum of the component settings must be constant (e.g., 100%). Statistica generates the standard simplex-lattice and simplex-centroid designs, and can handle lower bound restrictions on the components (for lower and upper bound restrictions, select Designs for constrained surfaces and mixtures on the Advanced tab). The results can be computed for the original component settings as well as the pseudo-component. For more information concerning these designs, refer to the Introductory Overview.

Note: most of these designs can also be analyzed via General Linear Models (GLM) or General Regression Models (GRM), or via (nonlinear) Generalized Linear/Nonlinear Models (GLZ).