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On testing hypothesis of fuzzy sample mean. (English) Zbl 1128.62061

Summary: In many expositions of fuzzy methods, fuzzy techniques are described as an alternative to a more traditional statistical approach. We present a class of fuzzy statistical decision processes in which testing hypothesis can be naturally reformulated in terms of interval-valued statistics. We provide the definitions of fuzzy mean, fuzzy distance as well as investigation of their related properties. We also give some empirical examples to illustrate the techniques and to analyze fuzzy data. Empirical studies show that fuzzy hypothesis testing with soft computing for interval data are more realistic and reasonable in the social sciences research. Finally certain comments are suggested for further studies. We hope that this reformation will make the corresponding fuzzy techniques more acceptable to researchers whose only experience is in using traditional statistical methods.

MSC:

62G10 Nonparametric hypothesis testing
62C99 Statistical decision theory
62G99 Nonparametric inference
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