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

Bootstrap Nonlinear Regression Application in a Design of an Experiment Data for Fewer Sample Size