The Bootstrap.

The article discusses statistics, which is a branch of applied mathematics that seeks to draw inferences from limited, incomplete, or imperfect data. The focus of the article is the various ways in which statisticians can reuse data to quantify the uncertainty of complex models. An overview of statistics is presented which includes a discussion on how statistical inference is used to estimate a given parameter, or to test a hypothesis related to them, and various origin myths of probability distributions, such as the origin of the Gaussian bell curve. Also discussed are fitting models, in which statisticians record a lot of data and fit it into an appropriate model, and bootstrapping, which approximates a sampling distribution with three sources of approximation errors.