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Vol 8, No 2:

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A Statistical Hypothesis Testing of Analysis of Variance for Two Way Classification in Fuzzy Environments
A. Mariappan , M. Pachamuthu
Abstract
The Analysis of Variance (ANOVA) is the most popular technique for testing of significance. ANOVA for one way classification model is a series of observations distributed over the different levels at single factor and the two-way classification model is the set of observations distributed over different levels of two simultaneous factors. In real-life situations, most of the observations cannot be recorded or collected precisely. A fuzzy environment is the decision-making process in which the goals and the constraints, but not necessarily the system under control, are fuzzy in nature. The two-way classification model is the collection of observations of two simultaneous variables distributed over challenging levels without the h-level concept of Trapezoidal Fuzzy Numbers (TZFNs). In this paper a statistical hypothesis testing of ANOVA two way classification with fuzzy environments through an numerical examples.
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ISSN(P) 2350-0174

ISSN(O) 2456-2378

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