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Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data.

Muhammad AslamOsama H Arif
Published in: Journal of analytical methods in chemistry (2020)
The Hotelling T-squared statistic has been widely used for the testing of differences in means for the multivariate data. The existing statistic under classical statistics is applied when observations in multivariate data are determined, precise, and exact. In practice, it is not necessary that all observations in the data are determined and precise due to measurement in complex situations and under uncertainty environment. In this paper, we will introduce the Hotelling T-squared statistic under neutrosophic statistics (NS) which is the generalization of classical statistics and applied under uncertainty environment. We will discuss the application and advantage of the neutrosophic Hotelling T-squared statistic with the aid of data. From the comparison, we will conclude that the proposed statistic is more adequate and effective in uncertainty.
Keyphrases
  • electronic health record
  • data analysis
  • big data
  • healthcare
  • deep learning
  • density functional theory