Introduction:The bootstrap method is commonly used to estimate values linked with estimator and test statistical sampling distributions. As a result, it is required to have a good manner of calculating with some improvement of the proposed strategy to maintain the proposed model's efficiency and accuracy. Objective: This study aimed to compare parameter estimates using SAS programming and determine the optimal computation for representing data using the bootstrapping and non-bootstrapping methods. Methods: In this study, the bootstrap method was applied using SAS programming. Results: In comparison to a model without bootstrapping, exponential growth demonstrates a very good model utilizing bootstrapping approach because the outcome provided the smallest standard error. This implies that the best model is the exponential model with bootstrapping approach. Conclusions: Finally, these prospective methodologies have resulted in the effective study and provide the best outcomes for decision making, particularly for decision-makers, among studies in their sector.
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