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  2. Bootstrap curriculum - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_curriculum

    Bootstrap is based at Brown University (USA), and builds on the research and development done there. Bootstrap curriculum consists of 4 research-based curricular computer science modules for grades 6-12. The 4 modules are Bootstrap:Algebra, Bootstrap:Reactive, Bootstrap:Data Science, and Bootstrap:Physics.

  3. Mobirise - Wikipedia

    en.wikipedia.org/wiki/Mobirise

    Mobirise is a freeware web design application that allows users to design and publish bootstrap websites without coding. [3] Mobirise is essentially a drag and drop website builder, [4] featuring various website themes. It is headquartered in Eindhoven, Netherlands.

  4. Neurath's boat - Wikipedia

    en.wikipedia.org/wiki/Neurath's_boat

    Keith Stanovich, in his book The Robot's Rebellion, refers to it as a Neurathian bootstrap, using bootstrapping as an analogy to the recursive nature of revising one's beliefs. [10] A "rotten plank" on the ship, for instance, might represent a meme virus or a junk meme (i.e., a meme that is either maladaptive to the individual, or serves no ...

  5. Particle filter - Wikipedia

    en.wikipedia.org/wiki/Particle_filter

    A particle filter's goal is to estimate the posterior density of state variables given observation variables. The particle filter is intended for use with a hidden Markov Model, in which the system includes both hidden and observable variables.

  6. Bootstrap current - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_current

    From a kinetic point of view, the bootstrap current is the effect of trapped particles (which practically lie on poloidal plane) and density gradient: the poloidal current due to trapped particles motion is unbalanced since the density is not constant, therefore the bootstrap current is needed to "close the circuit".

  7. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    The bootstrap can be used to construct confidence intervals for Pearson's correlation coefficient. In the "non-parametric" bootstrap, n pairs ( x i , y i ) are resampled "with replacement" from the observed set of n pairs, and the correlation coefficient r is calculated based on the resampled data.