Bootstrap is an important statistical method in non-parametric statistics that estimates the variability of statistics and can estimate the interval of statistics. It is also called the bootstrap method.
The core ideas and basic steps are as follows:
(1) Use repeated sampling technology to extract a certain number from the original sample (can be given by yourself, generally the same as the original sample same) sample, this process allows for repeated sampling.
(2) Calculate the statistic T to be estimated based on the extracted samples.
(3) Repeat the above N times (generally greater than 1000) to obtain N statistics T.
(4) Calculate the sample variance of the above N statistics T to estimate the variance of the statistic T.
It should be said that Bootstrap is a popular statistical method in modern statistics and works well in small samples. Confidence intervals can be constructed through the estimation of variance, and its application scope is further extended.
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