This distribution was called the bootstrap distribution of \(\overline{x}\). We stated at the time that the bootstrap distribution is an approximation to the sampling distribution of \(\overline{x}\) in the sense that both distributions will have a similar shape and similar spread. Thus the standard error of the bootstrap distribution can be used as an approximation to the standard error of the sampling distribution.