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  2. Bootstrapping (statistics) - Wikipedia

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

    The simplest bootstrap method involves taking the original data set of heights, and, using a computer, sampling from it to form a new sample (called a 'resample' or bootstrap sample) that is also of size N. The bootstrap sample is taken from the original by using sampling with replacement (e.g. we might 'resample' 5 times from [1,2,3,4,5] and ...

  3. Resampling (statistics) - Wikipedia

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

    Subsampling is an alternative method for approximating the sampling distribution of an estimator. The two key differences to the bootstrap are: the resample size is smaller than the sample size and; resampling is done without replacement. The advantage of subsampling is that it is valid under much weaker conditions compared to the bootstrap.

  4. Bootstrapping populations - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_populations

    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 ...

  5. Balanced repeated replication - Wikipedia

    en.wikipedia.org/wiki/Balanced_repeated_replication

    Calculate the statistic of interest for each half-sample. Estimate the variance of the statistic on the basis of differences between the full-sample and half-sample values. Selection of half-samples Simplified version. Consider first an idealized situation, where each stratum of our sample contains only two units.

  6. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    A bootstrap creates numerous simulated samples by randomly resampling (with replacement) the original, combined sample data, assuming the null hypothesis is correct. The bootstrap is very versatile as it is distribution-free and it does not rely on restrictive parametric assumptions, but rather on empirical approximate methods with asymptotic ...

  7. 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 ...

  8. Homoscedasticity and heteroscedasticity - Wikipedia

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

    Plot with random data showing homoscedasticity: at each value of x, the y-value of the dots has about the same variance. Plot with random data showing heteroscedasticity: The variance of the y-values of the dots increases with increasing values of x.

  9. Cluster sampling - Wikipedia

    en.wikipedia.org/wiki/Cluster_sampling

    In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this sampling plan, the total population is divided into these groups (known as clusters) and a simple random sample of the groups is ...