A New Mood’s Median Test for Imprecise Data

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Abdulrahman AlAita, Muhammad Aslam, Florentin Smarandache


The existing Mood’s median test is a non-parametric test used to compare two or more sample data sets whether they are from the same population or not. There can be no application of this test to uncertain and indeterminate data. Therefore, it is necessary to find a generalization of this test that will enable us to apply it in uncertain environments. This study will present a new approach that utilizes neutrosophic statistics to apply Mood’s median test. The approach involves defining hypotheses, determining a decision rule, and performing the test in an uncertain environment. An evaluation of the performance of the proposed test will be conducted using numerical examples. The results reveal that the proposed test under neutrosophic statistics is more informative, efficient, and flexible than the existing test under classical statistics in the presence of uncertain data.

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