It has been suggested that this article or section be merged with Bootstrap (statistics). (Discuss)

In statistics, bootstrapping is a method for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. It is distinguished from the jackknife procedure, used to detect outliers, and cross-validation, used to make sure that results are repeatable. There are more complicated bootstraps for sampling without replacement, two-sample problems, regression, time series, hierarchical sampling, mediation analyses, and other statistical problems. Wikipedia does not have an article with this exact name. ... In statistics, bootstrapping is a modern, computer intensive, general purpose approach to statistical inference, falling within a broader class of resampling methods. ... Template:Otherusescccc A graph of a bell curve in a normal distribution showing statistics used in educational assessment, comparing various grading methods. ... In statistics, a sampling distribution is the probability distribution, under repeated sampling of the population, of a given statistic (a numerical quantity calculated from the data values in a sample). ... In statistics, an estimator is a function of the observable sample data that is used to estimate an unknown population parameter; an estimate is the result from the actual application of the function to a particular set of data. ... Resampling is a term used in statistics to describe a variety of methods for computing summary statistics using subsets of available data (jackknife), drawing randomly with replacement from a set of data points (bootstrapping), or switching labels on data points when performing significance tests (permutation test, also called exact test... Resampling is a term used in statistics to describe a variety of methods for computing summary statistics using subsets of available data (jackknife), drawing randomly with replacement from a set of data points (bootstrapping), or switching labels on data points when performing significance tests (permutation test, also called exact test... In statistics, an outlier is a single observation far away from the rest of the data. ... In statistics cross-validation is the practice of partitioning a sample of data into subsamples such that analysis is initially performed on a single subsample, while further subsamples are retained blind in order for subsequent use in confirming and validating the initial analysis. ...

Bootstrapping [1] [2] is becoming the most popular method of testing mediation because it does not require the normality assumption to be met, and because it can be effectively utilized with smaller sample sizes (N < 20). However, mediation continues to be (perhaps inappropriately) most frequently determined using (1) the logic of Baron and Kenny [3] or (2) the Sobel test.

For more details see bootstrap resampling. Resampling is a term used in statistics to describe a variety of methods for computing summary statistics using subsets of available data (jackknife), drawing randomly with replacement from a set of data points (bootstrapping), or switching labels on data points when performing significance tests (permutation test, also called exact test...

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References

• Bradley Efron (1979). "Bootstrap Methods: Another Look at the Jackknife". The Annals of Statistics 7 (1): 1–26.
• Bradley Efron; Robert Tibshirani (1994). An Introduction to the Bootstrap. Chapman & Hall/CRC.  [4]

bootstraping dd Bradley Efron is a statistician best known for proposing the bootstrap resampling technique, which has had a major impact in the field of Statistics and virtually every area of statistical application. ...