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  2. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]

  3. Distance sampling - Wikipedia

    en.wikipedia.org/wiki/Distance_sampling

    Distance sampling is a widely used group of closely related methods for estimating the density and/or abundance of populations. The main methods are based on line transects or point transects .

  4. Bootstrapping (statistics) - Wikipedia

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

    A way to improve on the Poisson bootstrap, termed "sequential bootstrap", is by taking the first samples so that the proportion of unique values is ≈0.632 of the original sample size n. This provides a distribution with main empirical characteristics being within a distance of (/). [36]

  5. Statistical distance - Wikipedia

    en.wikipedia.org/wiki/Statistical_distance

    In statistics, probability theory, and information theory, a statistical distance quantifies the distance between two statistical objects, which can be two random variables, or two probability distributions or samples, or the distance can be between an individual sample point and a population or a wider sample of points. A distance between ...

  6. Earth mover's distance - Wikipedia

    en.wikipedia.org/wiki/Earth_mover's_distance

    In computer science, the earth mover's distance (EMD) [1] is a measure of dissimilarity between two frequency distributions, densities, or measures, over a metric space D.

  7. Sampling (statistics) - Wikipedia

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

    For example, suppose we wish to sample people from a long street that starts in a poor area (house No. 1) and ends in an expensive district (house No. 1000). A simple random selection of addresses from this street could easily end up with too many from the high end and too few from the low end (or vice versa), leading to an unrepresentative sample.

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  9. Jackknife resampling - Wikipedia

    en.wikipedia.org/wiki/Jackknife_resampling

    Given a sample of size , a jackknife estimator can be built by aggregating the parameter estimates from each subsample of size () obtained by omitting one observation. [ 1 ] The jackknife technique was developed by Maurice Quenouille (1924–1973) from 1949 and refined in 1956.

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