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  2. Fractional factorial design - Wikipedia

    en.wikipedia.org/wiki/Fractional_factorial_design

    Fractional designs are expressed using the notation l k − p, where l is the number of levels of each factor, k is the number of factors, and p describes the size of the fraction of the full factorial used. Formally, p is the number of generators; relationships that determine the intentionally confounded effects that reduce the number of runs ...

  3. Yates analysis - Wikipedia

    en.wikipedia.org/wiki/Yates_Analysis

    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 ...

  4. Aliasing (factorial experiments) - Wikipedia

    en.wikipedia.org/wiki/Aliasing_(factorial...

    A fractional factorial design is said to have resolution if every -factor effect [note 4] is unaliased with every effect having fewer than factors. For example, a design has resolution R = 3 {\displaystyle R=3} if main effects are unaliased with each other (taking p = 1 ) {\displaystyle p=1)} , though it allows main effects to be aliased with ...

  5. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    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.

  6. Plackett–Burman design - Wikipedia

    en.wikipedia.org/wiki/Plackett–Burman_design

    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]

  7. Orthogonal array - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_Array

    An orthogonal array can be used to design a fractional factorial experiment. The columns represent the various factors and the entries are the levels at which the factors are observed. An experimental run is a row of the orthogonal array, that is, a specific combination of factor levels.

  8. ‘This Is Not A Love Story’ by Huffington Post

    testkitchen.huffingtonpost.com/this-is-not-a...

    A scary, sobering look at fatal domestic violence in the United States

  9. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Design of experiments with full factorial design (left), response surface with second-degree polynomial (right) The design of experiments , also known as experiment design or experimental design , is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation.