中文摘要：

以模糊集合理论为依据,提出一种新的假设检验方法——非统计假设检验.这种方法可以从少量的采样数据出发,用线性估计法自动识别总体分布的隶属函数,并直接估计出总体分布的真值及其分布区间.根据模糊集合理论建立了用隶属度描述的假设检验否定域,通过大量案例与统计方法进行对比分析,表明所提出的非统计假设检验方法具有很好的检验效果,置信度达到95%.

英文摘要：

Based on fuzzy-set theory, a novel method of hypothesis testing is proposed to solve some problems of traditional statistics. This method is named as the non-statistical hypothesis testing. Started with small sample data, the membership function of the distribution of a collectivity can be recognized automatically, and the true value including its distribution interval of the collectivity can also be estimated directly by the linear estimation method. The rejected region of hypothesis testing, characterized by a membership degree, is suggested by the use of fuzzy-set theory. Many cases are investigated by comparing with the statistical theory, some good efficacy by dint of the non-statistical hypothesis testing method proposed is validated, and the approximate 95% confidence level is yielded.