In traditional statistics, all parameters are defined from mathematical models andexperimental observations. Sometimes such assumptions seem to be strict foreveryday life issues. Especially if they are dealing with linguistic data or needs thatare not explicit. To solve this problem, the fuzzy method is used. In this dissertation,in the first stage of research, considering the different types of phenomena (biotechnical, physical-social), the hypotheses related to these phenomena are oftenformulated. Then, during the second stage, the hypotheses that are confirmed orrejected are collected and analyzed. Mathematical statistical methods are used whenthe hypothesis is probabilistic in nature, ie the phenomenon under study is describedby a probabilistic model. These methods do not statistically test and allow events thatare often unlikely to be determined when the statistical assumption is correct. Thehypothesis test is then performed when both the data and the parameter are fuzzy.Then different types of fuzzy hypotheses are introduced and the point estimationmethod based on maximum likelihood in fuzzy sets is described. Fuzzy is made. Inthe following sections, the fuzzy hypothesis test for the mean and the variance of thenormal distribution separately and the fuzzy hypothesis test for the mean exponentialdistribution in the form of α-sections of the fuzzy test statistic appropriate to eachproblem are examined, respectively
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Application of Fuzzy Statistics in Statistical Tests
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