  This paper reports on application of bootstrap nonlinear regression method to
a design of an experiment dataset with fewer experimental runs. Design with
desired properties was augmented and verified using graphical techniques. The
augmented design with the desired properties benefited the accuracy of the
approximated function used. The computation power of R-language and SAS for
computing nonlinear function and bootstrap was also compared.
