Abstract
ABSTRACT This paper proposes an alternative p-value test approach to proceed statistical tests of mean for normal population with fuzzy data. In real-world applications, the approach is often used in tests of average quality characteristics in manufacturing environments. In the proposed approach, the membership function of fuzzy test statistic is first constructed based on the α-cuts of fuzzy numbers. Since the function relationship between fuzzy test statistic and fuzzy data under known population variance is different from that under unknown population variance, we use two methods to construct the membership function under known and unknown population variance environment respectively. An alternative p-value is then calculated according to this membership function. Consequently, a statistical decision can be made by comparing the alternative p-value with the significance level. Two numerical examples are given for illustration.
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