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Designed experiments with full factorial design (left), response surface with second-degree polynomial (right) In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors.
Table of signs to calculate the effect estimates for a 3-level, 2-factor factorial design. Adapted from Berger et al., ch. 9. The full table of signs for a three-factor, two-level design is given to the right. Both the factors (columns) and the treatment combinations (rows) are written in Yates' order.
English: The table of signs for a 3-factor, 2-level factorial design used to calculate the effect estimates for each treatment combination. Date: 30 November 2017:
The settings for a two-level factorial design for the three factors in the implant step are denoted (A, B, C), and a two-level factorial design for the three factors in the anneal step are denoted (D, E, F). Also present are interaction effects between the implant factors and the anneal factors. Therefore, this experiment contains three sizes ...
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 ...
If N is a power of 2, however, the resulting design is identical to a fractional factorial design, so Plackett–Burman designs are mostly used when N is a multiple of 4 but not a power of 2 (i.e. N = 12, 20, 24, 28, 36 …). [3]
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.
As with all fractions constructed from Hadamard matrices, they have strength 2, and therefore resolution 3. [61] The smallest such design has 11 factors and 12 runs (treatment combinations), and is displayed in the article on such designs. Since 2 is its maximum strength, [note 9] 3 is its maximum resolution. Some detail about its aliasing ...