Abstract
A problem of defuzzification of a fuzzy test for testing statistical hypotheses with vague data is considered. Two defuzzification operators are discussed. It is shown that the superposition of a fuzzy test and these operators leads to decision strategies equivalent to the classical crisp tests. Moreover, another source of randomization in hypothesis testing is indicated, and a new ground for the randomized tests application is given. Advice to practitioners – how to defuzzify – is also given.
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