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  2. Fractional factorial design - Wikipedia

    en.wikipedia.org/wiki/Fractional_factorial_design

    The results of that example may be used to simulate a fractional factorial experiment using a half-fraction of the original 2 4 = 16 run design. The table shows the 2 4-1 = 8 run half-fraction experiment design and the resulting filtration rate, extracted from the table for the full 16 run factorial experiment.

  3. Yates analysis - Wikipedia

    en.wikipedia.org/wiki/Yates_Analysis

    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 special structure of these designs to generate least squares estimates for factor effects for ...

  4. 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.

  5. Aliasing (factorial experiments) - Wikipedia

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

    In a fractional factorial experiment, the contrast vectors belonging to a given effect are restricted to the treatment combinations in the fraction. Thus, in the half-fraction {11, 12, 13} in the 2 × 3 example, the three effects may be represented by the column vectors in the following table:

  6. Factorial number system - Wikipedia

    en.wikipedia.org/wiki/Factorial_number_system

    The factorial number system is sometimes defined with the 0! place omitted because it is always zero (sequence A007623 in the OEIS). In this article, a factorial number representation will be flagged by a subscript "!". In addition, some examples will have digits delimited by a colon. For example, 3:4:1:0:1:0! stands for

  7. Plackett–Burman design - Wikipedia

    en.wikipedia.org/wiki/Plackett–Burman_design

    Plackett–Burman designs are experimental designs presented in 1946 by Robin L. Plackett and J. P. Burman while working in the British Ministry of Supply. [1] Their goal was to find experimental designs for investigating the dependence of some measured quantity on a number of independent variables (factors), each taking L levels, in such a way as to minimize the variance of the estimates of ...

  8. Central composite design - Wikipedia

    en.wikipedia.org/wiki/Central_composite_design

    A factorial (perhaps fractional) design in the factors studied, each having two levels; A set of center points, experimental runs whose values of each factor are the medians of the values used in the factorial portion. This point is often replicated in order to improve the precision of the experiment;

  9. Double factorial - Wikipedia

    en.wikipedia.org/wiki/Double_factorial

    Toggle the table of contents. ... the double factorial of a ... and (−5)!! = ⁠ 1 / 3 ⁠; negative odd numbers with greater magnitude have fractional double ...