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  2. Generalized randomized block design - Wikipedia

    en.wikipedia.org/wiki/Generalized_randomized...

    In randomized statistical experiments, generalized randomized block designs (GRBDs) are used to study the interaction between blocks and treatments. For a GRBD, each treatment is replicated at least two times in each block; this replication allows the estimation and testing of an interaction term in the linear model (without making parametric ...

  3. Blocking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Blocking_(statistics)

    This is a workable experimental design, but purely from the point of view of statistical accuracy (ignoring any other factors), a better design would be to give each person one regular sole and one new sole, randomly assigning the two types to the left and right shoe of each volunteer. Such a design is called a "randomized complete block design."

  4. Box–Behnken design - Wikipedia

    en.wikipedia.org/wiki/Box–Behnken_design

    Each design can be thought of as a combination of a two-level (full or fractional) factorial design with an incomplete block design. In each block, a certain number of factors are put through all combinations for the factorial design, while the other factors are kept at the central values. For instance, the Box–Behnken design for 3 factors ...

  5. Randomized block design - Wikipedia

    en.wikipedia.org/?title=Randomized_block_design&...

    Randomized block design. 1 language. ... Download QR code; Print/export Download as PDF; Printable version; In other projects Wikidata item; Appearance.

  6. Completely randomized design - Wikipedia

    en.wikipedia.org/wiki/Completely_randomized_design

    In the design of experiments, completely randomized designs are for studying the effects of one primary factor without the need to take other nuisance variables into account. This article describes completely randomized designs that have one primary factor.

  7. Full factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Full_factorial_experiment

    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] Alternative strategies with improved computational efficiency include fractional factorial designs, Latin hypercube sampling, and quasi-random sampling techniques.

  8. Replication (statistics) - Wikipedia

    en.wikipedia.org/wiki/Replication_(statistics)

    In engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions to support the original claim, which is crucial to confirm the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]

  9. Template:Numbered block/sandbox - Wikipedia

    en.wikipedia.org/wiki/Template:Numbered_block/...

    This template creates a numbered block which is usually used to number mathematical and chemical formulae. This template can be used together with {{EquationRef}} and {{EquationNote}} to produce formatted numbered equations if a back reference to an equation is wanted.