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  2. Completely randomized design - Wikipedia

    en.wikipedia.org/wiki/Completely_randomized_design

    The model for the response is , = + + with Y i,j being any observation for which X 1 = i (i and j denote the level of the factor and the replication within the level of the factor, respectively) μ (or mu) is the general location parameter; T i is the effect of having treatment level i

  3. Repeated measures design - Wikipedia

    en.wikipedia.org/wiki/Repeated_measures_design

    Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. [1] For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed.

  4. Design effect - Wikipedia

    en.wikipedia.org/wiki/Design_effect

    This quantity reflects what would be the sample size that is needed to achieve the current variance of the estimator (for some parameter) with the existing design, if the sample design (and its relevant parameter estimator) were based on a simple random sample. [10] A related quantity is the effective sample size ratio, which can be calculated ...

  5. Box–Behnken design - Wikipedia

    en.wikipedia.org/wiki/Box–Behnken_design

    The design should be sufficient to fit a quadratic model, that is, one containing squared terms, products of two factors, linear terms and an intercept. The ratio of the number of experimental points to the number of coefficients in the quadratic model should be reasonable (in fact, their designs kept in the range of 1.5 to 2.6).

  6. Response surface methodology - Wikipedia

    en.wikipedia.org/wiki/Response_surface_methodology

    The engineers had not been able to afford to fit a cubic three-level design to estimate a quadratic model, and their biased linear-models estimated the gradient to be zero. Box's design reduced the costs of experimentation so that a quadratic model could be fit, which led to a (long-sought) ascent direction. [3] [4]

  7. Surrogate model - Wikipedia

    en.wikipedia.org/wiki/Surrogate_model

    A surrogate model is an engineering method used when an outcome of interest cannot be easily measured or computed, so an approximate mathematical model of the outcome is used instead. Most engineering design problems require experiments and/or simulations to evaluate design objective and constraint functions as a function of design variables.

  8. Sampling design - Wikipedia

    en.wikipedia.org/wiki/Sampling_design

    In business research, companies must often generate samples of customers, clients, employees, and so forth to gather their opinions. Sample design is also a critical component of marketing research and employee research for many organizations. During sample design, firms must answer questions such as:

  9. Optimal experimental design - Wikipedia

    en.wikipedia.org/wiki/Optimal_experimental_design

    The optimality of a design depends on the statistical model and is assessed with respect to a statistical criterion, which is related to the variance-matrix of the estimator. Specifying an appropriate model and specifying a suitable criterion function both require understanding of statistical theory and practical knowledge with designing ...