A normally distributed data set of 1,000 values--ranging from 50 to 150, with a mean of 50 and a standard deviation of 20--was created in order to evaluate the bootstrap method of repeated random sampling. Nine bootstrap samples of N=10 and nine more bootstrap samples of N=25 were randomly selected. One thousand random samples were selected from each of the 18 bootstrap samples, and its mean and standard deviation were calculated. The cumulative means and standard deviations diverged from the parameter values as often, and to the same extent, as they converged toward them. It was also concluded that the bootstrap procedure was biased because it did not continue to approach the universe parameter as the number of iterations increased. The limit of convergence was not the universe parameter. Hence, the bootstrap hypothesis regarding point estimates of means and standard deviations was not supported. (Author/GDC)