Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Researchs - Department of Operations Research

In this study, an approach is developed to solve the problem of non-decision and statistical hypothesis tests when test statistics (decision making under uncertainty) occur as a result of the test cloudy region in one-sample test in case of two tailed in the cases of crisp and fuzzy through optimizing type II error. Bootstrap approach is used in the crisp case because it is a simple method for calculating some of the famous statistics such as confidence interval (CI), testing of hypothesis, calculating approximated biases and so forth. The developed approach employs some of the statistics that have been calculated from through Bootstrap in determining acceptance and rejection regions and explore the magnitude of the problem that in the case of certainty or in the uncertainty. In the fuzzy case, the membership function is constructed and the critical areas under H0 and H1. Also, the linguistic testing of hypothesis formulation developed in fuzzy case

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