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  2. Bootstrapping (statistics) - Wikipedia

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

    The studentized bootstrap, also called bootstrap-t, is computed analogously to the standard confidence interval, but replaces the quantiles from the normal or student approximation by the quantiles from the bootstrap distribution of the Student's t-test (see Davison and Hinkley 1997, equ. 5.7 p. 194 and Efron and Tibshirani 1993 equ 12.22, p. 160):

  3. Bootstrap (front-end framework) - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_(front-end...

    Bootstrap (formerly Twitter Bootstrap) is a free and open-source CSS framework directed at responsive, mobile-first front-end web development. It contains HTML , CSS and (optionally) JavaScript -based design templates for typography , forms , buttons , navigation , and other interface components.

  4. Resampling (statistics) - Wikipedia

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

    The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...

  5. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    The bootstrap dataset is made by randomly picking objects from the original dataset. Also, it must be the same size as the original dataset. However, the difference is that the bootstrap dataset can have duplicate objects. Here is a simple example to demonstrate how it works along with the illustration below:

  6. Out-of-bag error - Wikipedia

    en.wikipedia.org/wiki/Out-of-bag_error

    One set, the bootstrap sample, is the data chosen to be "in-the-bag" by sampling with replacement. The out-of-bag set is all data not chosen in the sampling process. When this process is repeated, such as when building a random forest, many bootstrap samples and OOB sets are created. The OOB sets can be aggregated into one dataset, but each ...

  7. Bootstrap error-adjusted single-sample technique - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_error-adjusted...

    In statistics, the bootstrap error-adjusted single-sample technique (BEST or the BEAST) is a non-parametric method that is intended to allow an assessment to be made of the validity of a single sample.

  8. Pagination - Wikipedia

    en.wikipedia.org/wiki/Pagination

    Pagination, also known as paging, is the process of dividing a document into discrete pages, either electronic pages or printed pages.. In reference to books produced without a computer, pagination can mean the consecutive page numbering to indicate the proper order of the pages, which was rarely found in documents pre-dating 1500, and only became common practice c. 1550, when it replaced ...

  9. Engelbart's law - Wikipedia

    en.wikipedia.org/wiki/Engelbart's_Law

    Engelbart's law is the observation that the intrinsic rate of human performance is exponential. [further explanation needed] The law is named after Douglas Engelbart, whose work in augmenting human performance was explicitly based on the realization that although we use technology, the ability to improve on improvements (bootstrapping, "getting better at getting better") resides entirely ...