M. KHADEMI - DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE, SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN
V. AMIRZADEH - DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER SCIENCE, SHAHID BAHONAR UNIVERSITY OF KERMAN, IRAN

There are many situations for statistical process in which we have both random and vagueinformation. When uncertainty is due to fuzziness of information, fuzzy statistical control charts play animportant role in the monitoring process, because they simultaneously deal with both kinds of uncertainty.Dealing with fuzzy characteristics using classical methods may cause the loss of information and inuencein process deciding making. In this paper, we proposed a decision-making process based on fuzzy rejectionregions and fuzzy statistical tests for crisp observation. With both methods, we de ne the degree of depen-dence to acceptance region for decision in the fuzzy regions and process fuzzy. A numeric example illustratesthe performance of the method and interprets the results.

fuzzy hypotheses testing, fuzzy rejection region, hybrid numbers