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Each generator halves the number of runs required. A design with p such generators is a 1/(l p)=l −p fraction of the full factorial design. [3] For example, a 2 5 − 2 design is 1/4 of a two-level, five-factor factorial design. Rather than the 32 runs that would be required for the full 2 5 factorial experiment, this experiment requires only ...
A full factorial design contains all possible combinations of low/high levels for all the factors. A fractional factorial design contains a carefully chosen subset of these combinations. The criterion for choosing the subsets is discussed in detail in the fractional factorial designs article. Formalized by Frank Yates, a Yates analysis exploits ...
The extent of aliasing in a given fractional design is measured by the resolution of the fraction, a concept first defined by Box and Hunter: [5] A fractional factorial design is said to have resolution if every -factor effect [note 4] is unaliased with every effect having fewer than factors.
Stat-Ease released its first version of Design–Expert in 1988. In 1996 the firm released version 5 which was the first version of the software designed for Microsoft Windows. [3] Version 6.0 moved to a full 32-bit architecture and fuller compliance with Windows visual convention and also allowed up to 256 runs for two-level blocked designs. [4]
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Statisticians [2] [3] describe stronger multifactorial DOE methods as being more “robust”: see Experimental design. As DOE software advancements gave rise to solving complex factorial statistical equations, statisticians began in earnest to design experiments with more than one factor (multifactor) being tested at a time.
This experiment is an example of a 2 2 (or 2×2) factorial experiment, so named because it considers two levels (the base) for each of two factors (the power or superscript), or #levels #factors, producing 2 2 =4 factorial points. Cube plot for factorial design . Designs can involve many independent variables.
For instance, consider a scenario with three factors, each having two levels, and an experiment that tests every possible combination of these levels (a full factorial design). One complete replication of this design would comprise 8 runs (2^3). The design can be executed once or with several replicates. [2]