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  2. Replication (statistics) - Wikipedia

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

    Example of direct replication and conceptual replication. There are two main types of replication in statistics. First, there is a type called “exact replication” (also called "direct replication"), which involves repeating the study as closely as possible to the original to see whether the original results can be precisely reproduced. [3]

  3. Reproducibility - Wikipedia

    en.wikipedia.org/wiki/Reproducibility

    Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.

  4. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [13] by Abraham Wald in the context of sequential tests of statistical hypotheses. [14]

  5. Replicate (biology) - Wikipedia

    en.wikipedia.org/wiki/Replicate_(biology)

    This biology article is a stub. You can help Wikipedia by expanding it.

  6. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

  7. Factorial experiment - Wikipedia

    en.wikipedia.org/wiki/Factorial_experiment

    Factorial experiments are described by two things: the number of factors, and the number of levels of each factor. For example, a 2×3 factorial experiment has two factors, the first at 2 levels and the second at 3 levels. Such an experiment has 2×3=6 treatment combinations or cells.

  8. Single-subject design - Wikipedia

    en.wikipedia.org/wiki/Single-subject_design

    Researchers use single-subject design because these designs are sensitive to individual organism differences vs group designs which are sensitive to averages of groups. The logic behind single subject designs is 1) Prediction, 2) Verification, and 3) Replication. The baseline data predicts behaviour by affirming the consequent.

  9. Experiment (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Experiment_(probability...

    A random experiment that has exactly two (mutually exclusive) possible outcomes is known as a Bernoulli trial. [ 2 ] When an experiment is conducted, one (and only one) outcome results— although this outcome may be included in any number of events , all of which would be said to have occurred on that trial.