A statistical technique. Bootstrapping involves pooling the data from two samples and drawing samples repeatedly from the pool, with replacement, to create a single distribution. The number of samplings taken to create the distribution is typically in the thousands. Then the two original samples are compared using this grand distribution as an estimate of the true population to determine whether they are significantly different from one another. Bootstrapping has been applied both to PDD and brain wave approaches. See: Farwell & Donchin (1988); Honts & Devitt (1992); MacLaren & Taukulis (2000).
