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Journal of Applied Mathematics
Volume 2015, Article ID 365304, 8 pages
Research Article

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

1Department of Mathematics, PSNA College of Engineering and Technology, Dindigul, Tamilnadu 624 622, India
2Department of Mathematics, Thiagarajar College of Engineering, Madurai, Tamilnadu 625015, India
3P.G. & Research Department of Mathematics, H.H. The Rajah’s College, Pudukkottai, Tamilnadu 622 001, India

Received 26 June 2014; Revised 1 September 2014; Accepted 3 September 2014

Academic Editor: Soo-Kyun Kim

Copyright © 2015 Manikandan Harikrishnan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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 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.