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  2. 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.

  3. Between-group design experiment - Wikipedia

    en.wikipedia.org/wiki/Between-group_design...

    A way to design psychological experiments using both designs exists and is sometimes known as "mixed factorial design". [3] In this design setup, there are multiple variables, some classified as within-subject variables, and some classified as between-group variables. [3] One example study combined both variables.

  4. Dynamic causal modeling - Wikipedia

    en.wikipedia.org/wiki/Dynamic_causal_modeling

    To enable efficient estimation of driving and modulatory effects, a 2x2 factorial experimental design is often used - with one factor serving as the driving input and the other as the modulatory input. [2] Resting state experiments have no experimental manipulations within the period of the neuroimaging recording.

  5. File:Table of signs for 3-factor, 2-level factorial design.png

    en.wikipedia.org/wiki/File:Table_of_signs_for_3...

    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

  6. Response surface methodology - Wikipedia

    en.wikipedia.org/wiki/Response_surface_methodology

    Once it is suspected that only significant explanatory variables are left, then a more complicated design, such as a central composite design can be implemented to estimate a second-degree polynomial model, which is still only an approximation at best. However, the second-degree model can be used to optimize (maximize, minimize, or attain a ...

  7. 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 ...

  8. 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 ...

  9. Multifactor design of experiments software - Wikipedia

    en.wikipedia.org/wiki/Multifactor_Design_of...

    Factorial experimental design software drastically simplifies previously laborious hand calculations needed before the use of computers. During World War II, a more sophisticated form of DOE, called factorial design, became a big weapon for speeding up industrial development for the Allied forces. These designs can be quite compact, involving a