n. a statistical procedure used to estimate the variability of a
parameter associated with a set of data, such as the
standard error or
confidence interval. It is particularly appropriate when the
variance or underlying distribution is not known. A number of samples are obtained from the original data by eliminating one or more observations at a time, the parameter in question is calculated for each sample, and the individual parameters are combined to provide an estimate of the overall parameter for the entire data set. A jackknife is similar to
bootstrapping, except that bootstrapping involves replacing observations after they have been sampled, such that after each observation is chosen it is reinserted into the data for possible selection again.