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2015 An Introduction to Fuzzy Testing of Multialternative Hypotheses for Group of Samples with the Single Parameter: Through the Fuzzy Confidence Interval of Region of Acceptance
Manikandan Harikrishnan, Jeyabharathi Sundarrajan, Muthuraj Rengasamy
J. Appl. Math. 2015: 1-8 (2015). DOI: 10.1155/2015/365304

Abstract

Classical statistics and many data mining methods rely on “statistical significance” as a sole criterion for evaluating alternative hypotheses. It is very useful to find out the significant difference existing between the samples as well as the population or between two samples. But in this paper, the researchers try to apply the concepts of fuzzy group testing of hypothesis problem between multi group of samples of same size or different, through comparing the parameters like mean, standard deviation, and so forth. Hence we can compare multigroups such that they have the significant difference in their mean or standard deviation or other parameters through the fuzzy group testing of multihypotheses. The authors introduced and investigated the concepts very first time through fuzzy analysis that can decide which group(s) or samples can be taken for further investigation and either H 0 is rejected or accepted and hence the next discussion provides the properties of group of samples which may result in the optimized solution for the problem.

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Manikandan Harikrishnan. Jeyabharathi Sundarrajan. Muthuraj Rengasamy. "An Introduction to Fuzzy Testing of Multialternative Hypotheses for Group of Samples with the Single Parameter: Through the Fuzzy Confidence Interval of Region of Acceptance." J. Appl. Math. 2015 1 - 8, 2015. https://doi.org/10.1155/2015/365304

Information

Published: 2015
First available in Project Euclid: 15 April 2015

zbMATH: 06640989
Digital Object Identifier: 10.1155/2015/365304

Rights: Copyright © 2015 Hindawi

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