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  2. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Design of experiments with full (left), with second-degree polynomial (right) The design of experiments ( DOE or DOX ), 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 reflect the variation.

  3. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to ...

  4. Yates analysis - Wikipedia

    en.wikipedia.org/wiki/Yates_Analysis

    In statistics, a Yates analysis is an approach to analyzing data obtained from a designed experiment, where a factorial design has been used. Full- and fractional-factorial designs are common in designed experiments for engineering and scientific applications. In these designs, each factor is assigned two levels, typically called the low and ...

  5. Response surface methodology - Wikipedia

    en.wikipedia.org/wiki/Response_surface_methodology

    Response surface methodology. In statistics, response surface methodology ( RSM) explores the relationships between several explanatory variables and one or more response variables. RSM is an empirical model which employs the use of mathematical and statistical techniques to relate input variables, otherwise known as factors, to the response.

  6. Blocking (statistics) - Wikipedia

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

    Blocking (statistics) In the statistical theory of the design of experiments, blocking is the arranging of experimental units that are similar to one another in groups (blocks) based on one or more variables. These variables are chosen carefully to minimize the impact of their variability on the observed outcomes.

  7. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    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. A full factorial design may also be called a fully crossed design.

  8. Multifactor design of experiments software - Wikipedia

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

    Multifactor design of experiments software. Software that is used for designing factorial experiments plays an important role in scientific experiments and represents a route to the implementation of design of experiments procedures that derive from statistical and combinatorial theory. In principle, easy-to-use design of experiments (DOE ...

  9. Replication (statistics) - Wikipedia

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

    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 crucial to confirm the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]

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