Bootstrap: The data-based simulation method/technique for the statistical inference which can be used to study the variability of the estimated characteristics of the probability distribution of a set of observations and give con?dence intervals for the parameters in situations where these are difficult or impossible to derive in the usual manner. (The use of term bootstrap derives from the phrase 'to pull oneself up by the one's bootstraps'.) The general idea and approach of the procedure involves sampling with the replacement to produce random samples of size n from the original data, x1; x2; ... ; xn; each of these is called as a bootstrap sample and each gives an approximate idea of the parameter of interest. Repeating the process the large number of times provides the desired information on the variability of the estimator and the approximate 95% con?dence interval can, for instance, be derived from the 2.5% and 97.5% quantiles of the replicate values.