1DEPARTMENT OF STATISTICS, FACULTY OF MATHEMATICS AND COMPUTER, SHAHID BAHONAR UNIVERSITY OF KERMAN, KERMAN, IRAN
2DEPARTMENT OF STATISTICS, HIGHER EDUCATION COMPLEX OF BAM, KERMAN, IRAN
Several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. In analysis of variance, when the response random variable Y , has linear relationship with several random variables X, another important model as analysis of covariance can be used. In this paper, assuming that Y is fuzzy and using DLR metric, a method for testing the linear hypothesis has been proposed based on fuzzy techniques. In fact, in this method a set of condence intervals has been used for creating fuzzy test statistic and fuzzy critical values. In addition, the proposed method has been mentioned for the reforming of the hypothesis testing when there is an uncertaity in accepting or rejecting hypotheses. Finally, by presenting two examples this method is illustrated. The result are illustrated by the means of some case studies.