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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 (electronics) - Wikipedia

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

    In the field of electronics, a technique where part of the output of a system is used at startup can be described as bootstrapping. A bootstrap circuit is one where part of the output of an amplifier stage is applied to the input, so as to alter the input impedance of the amplifier. When applied deliberately, the intention is usually to ...

  4. Responsive web design - Wikipedia

    en.wikipedia.org/wiki/Responsive_web_design

    Responsive web design ( RWD) or responsive design is an approach to web design that aims to make web pages render well on a variety of devices and window or screen sizes from minimum to maximum display size to ensure usability and satisfaction. [1] [2]

  5. CDC Implements Important New Regulation for All Dogs ... - AOL

    www.aol.com/cdc-implements-important-regulation...

    The Centers For Disease Control and Prevention announced new rules on Wednesday for traveling with a canine companion into the United States and these new rules go into effect on August 1.

  6. 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 ...

  7. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    For any non-linear model (for instance Logit and Probit models), however, heteroscedasticity has more severe consequences: the maximum likelihood estimates (MLE) of the parameters will usually be biased, as well as inconsistent (unless the likelihood function is modified to correctly take into account the precise form of heteroscedasticity or ...

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