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2. 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. As of May 2023, Bootstrap is the 17th most starred ...

3. Bootstrapping (statistics) - Wikipedia

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

   Bootstrapping (statistics) Bootstrapping is a procedure for estimating the distribution of an estimator by resampling (often with replacement) one's data or a model estimated from the data. [1] Bootstrapping assigns measures of accuracy (bias, variance, confidence intervals, prediction error, etc.) to sample estimates. [2][3] This technique ...

4. Help:A quick guide to templates - Wikipedia

   en.wikipedia.org/.../Help:A_quick_guide_to_templates

   Full details can be found in Help:Template, Wikipedia:Templates and m:Help:Advanced templates. A template is a Wikipedia page created to be included in other pages. It usually contains repetitive material that may need to show up on multiple articles or pages, often with customizable input. Templates sometimes use MediaWiki parser functions ...

5. Wikipedia:Templates - Wikipedia

   en.wikipedia.org/wiki/Wikipedia:Templates

   Wikipedia:Navigation templates, templates that link between multiple articles belonging to the same topic. Wikipedia:List of infoboxes for infoboxes, which are small panels that summarize key features of the page's subject. Wikipedia:Categorization for templates used for categories. Wikipedia:Citation templates for templates used to format ...

6. Bootstrapping populations - Wikipedia

   en.wikipedia.org/wiki/Bootstrapping_populations

   Bootstrapping populations in statistics and mathematics starts with a sample {, …,} observed from a random variable.. When X has a given distribution law with a set of non fixed parameters, we denote with a vector , a parametric inference problem consists of computing suitable values – call them estimates – of these parameters precisely on the basis of the sample.

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

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

   Bootstrap error-adjusted single-sample technique. 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. It is based on estimating a probability distribution representing what can be expected from ...