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A Statistical Analysis of Variance for One Way Classification with Addition Operations using Triangular Fuzzy Numbers

A. Mariappan, M. Pachamuthu

Abstract


The Analysis of Variance (ANOVA) is a statistical technique commonly used to compare several population means which exist simultaneously. The classical ANOVA model's statistical analysis infers about the rejection or acceptance of the null hypothesis at a certain level of significance. This paper proposes a novel computational method for implementing ANOVA for one way classification of fuzzy addition operations. Further, the extension principle is used with two Triangular Fuzzy Numbers (TFNs) with the -cut method based on decision rules to accept null hypothesis levels and illustrated with numerical examples.


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