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  2. Fractional factorial design - Wikipedia

    en.wikipedia.org/wiki/Fractional_factorial_design

    An important characteristic of a fractional design is the defining relation, which gives the set of interaction columns equal in the design matrix to a column of plus signs, denoted by I. For the above example, since D = AB and E = AC, then ABD and ACE are both columns of plus signs, and consequently so is BDCE: D*D = AB*D = I. E*E = AC*E = I

  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...

    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. List of statistics articles - Wikipedia

    en.wikipedia.org/wiki/List_of_statistics_articles

    These lists include items which are somehow related to statistics however are not included in this index: List of statisticians; List of important publications in statistics; List of scientific journals in statistics; Topic lists. Outline of statistics; List of probability topics; Glossary of probability and statistics; Glossary of experimental ...

  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.

  7. What That’s Really For: Items With Hidden Design Features - AOL

    www.aol.com/surprising-purpose-behind-everyday...

    In fact, many common items boast useful add-ons that can easily be mistaken for inconsequential elements of design, especially when they don't come with instructions.

  8. 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.

  9. Denise Richards Reveals Her Daughters 'Were Very Upset' She ...

    www.aol.com/denise-richards-reveals-her...

    Denise Richards is revealing what she did to get on her daughters’ bad side! The actress, 53, recently spoke with PEOPLE about her participation in the upcoming season of Special Forces: World ...