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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. Aliasing (factorial experiments) - Wikipedia

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

    [note 1] This necessitates limiting observations to a fraction (subset) of the treatment combinations. Aliasing is an automatic and unavoidable result of observing such a fraction. [3] [4] The aliasing properties of a design are often summarized by giving its resolution. This measures the degree to which the design avoids aliasing between main ...

  5. Central composite design - Wikipedia

    en.wikipedia.org/wiki/Central_composite_design

    The design matrix for a central composite design experiment involving k factors is derived from a matrix, d, containing the following three different parts corresponding to the three types of experimental runs: The matrix F obtained from the factorial experiment. The factor levels are scaled so that its entries are coded as +1 and −1.

  6. 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.

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  8. Conjoint analysis - Wikipedia

    en.wikipedia.org/wiki/Conjoint_analysis

    Example choice-based conjoint analysis survey with application to marketing (investigating preferences in ice-cream) Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes (feature, function, benefits) that make up an individual product or service.

  9. I usually hate yoga, but trying cat yoga changed my mind! - AOL

    www.aol.com/usually-hate-yoga-trying-cat...

    Instead, they're free to roam around or snooze in their cat beds while you practice your poses. You can give them a little stroke if they come near you. It's the same as a regular yoga class, just ...