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  2. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    Factorial designs allow the effects of a factor to be estimated at several levels of the other factors, yielding conclusions that are valid over a range of experimental conditions. The main disadvantage of the full factorial design is its sample size requirement, which grows exponentially with the number of factors or inputs considered. [6]

  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. 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 ( DOE ), [ 1 ] 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 ...

  5. Mixed-design analysis of variance - Wikipedia

    en.wikipedia.org/wiki/Mixed-design_analysis_of...

    Andy Field (2009) [1] provided an example of a mixed-design ANOVA in which he wants to investigate whether personality or attractiveness is the most important quality for individuals seeking a partner. In his example, there is a speed dating event set up in which there are two sets of what he terms "stooge dates": a set of males and a set of ...

  6. 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 ...

  7. Yates analysis - Wikipedia

    en.wikipedia.org/wiki/Yates_Analysis

    For example, the X 1 coefficient might change depending on whether or not an X 2 term was included in the model. This is not the case when the design is orthogonal, as is a 2 3 full factorial design. For orthogonal designs, the estimates for the previously included terms do not change as additional terms are added.

  8. Jack The Ripper’s Identity Revealed After 130 Years ... - AOL

    www.aol.com/lifestyle/took-them-137-years-jack...

    Over 130 years after his gruesome murders in East London, England, the descendants of his victims are looking to unmask the identity of the serial killer popularly known as Jack the Ripper. The ...

  9. 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 .