On detecting outliers in complex data using Dixon’s test under neutrosophic statistics

Abstract The existing Dixon’s test (DT) under classical statistics has been widely applied in a variety of fields. The main target of DT is to recognize the outlier or suspicious observation in the sample. The DT available in the literature is workable when all the observations in the sample or the population are precise, determined and certain. In practice, under the complex system, it may not possible that all observations in the data are determined. In such situations, the existing DT cannot be applied for the detection of the outlier value in the sample. In this paper, we will introduce a new Dixon’s test under the neutrosophic statistics is called (NDT). We will present the testing procedure for the proposed test using the neutrosophic statistical interval method. We will discuss its application with the help of an example.

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