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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.
In 2018, jQuery was used on 78% of the top 1 million websites. [19] In 2019, jQuery was used on 80% of the top 1 million websites (according to BuiltWith), [19] and 74.1% of the top 10 million (per W3Techs). [6] In 2021, jQuery was used on 77.8% of the top 10 million websites (according to W3Techs). [20]
jsDelivr is powered by other content delivery network providers, including Cloudflare, Fastly and BunnyCDN, and switches to another provider if one is experiencing downtime.
Free and open-source software portal jQuery UI is a collection of GUI widgets , animated visual effects, and themes implemented with jQuery (a JavaScript library ), Cascading Style Sheets , and HTML . [ 7 ]
jQuery Mobile provides a theming framework that allows developers to customize color schemes and certain CSS aspects of UI features. Developers can use the jQuery Mobile ThemeRoller [8] application to customize these appearances and create branded experiences. After developing a theme in the ThemeRoller application, programmers can download a ...
The concept of "unobtrusiveness" in relation to client-side JavaScript was coined in 2002 by Stuart Langridge [7] in the article "Unobtrusive DHTML, and the power of unordered lists". [8] In the article Langridge argued for a way to keep all JavaScript code, including event handlers, outside of the HTML when using dynamic HTML (DHTML). [ 7 ]
In general, bootstrapping usually refers to a self-starting process that is supposed to continue or grow without external input. Many analytical techniques are often called bootstrap methods in reference to their self-starting or self-supporting implementation, such as bootstrapping (statistics), bootstrapping (finance), or bootstrapping (linguistics).
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):