 we might 'resample' 5 times from [1,2,3,4,5] and get [2,5,4,4,1]), so, assuming "N" is sufficiently large, for all practical purposes there is virtually zero probability that it will be identical to the original "real" sample.This process is repeated a large number of times (typically 1,000 or 10,000 times), and for each of these bootstrap samples we compute its mean (each of these are called bootstrap estimates).We now can create a histogram of bootstrap means.