Extending Classical Unbiasedness Theory to Neutrosophic Data

The existing theory of unbiasedness, which aims to provide accurate and reliable estimates of the population in classical statistics, applies only when the data consists of precise and exact observations. Therefore, the classical method of unbiasedness cannot be used in the presence of uncertainty. In this paper, we modify the existing theory of unbiasedness using the concept of neutrosophic statistics. We present necessary theorems related to this new theory and introduce the theory of mean square error within the context of neutrosophy. We also provide application and simulation studies for the proposed method of unbiasedness. We demonstrate that the degree of uncertainty plays an important role in computing the expected value and compare the results of the proposed method with the classical unbiasedness method.