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Testing Hypothesis Concerning Correlation Coefficient with Fuzzy Data

机译:用模糊数据测试关于相关系数的假设

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Testing hypothesis of correlation coefficient is important in inference statistics.  The extension of the idea of correlation to fuzzy environments is of great interesting.  The aim of this work is to elucidate the test of hypothesis concerning correlation coefficient with fuzzy data. Theα-cuts of fuzzy sample correlation coefficient are first derived at various α-values.  The membership function of the fuzzy test statistic is then constructed based on these α-cuts.  The fuzzy probability of rejecting the null hypothesis is then determined using this membership function. For crisp data, this method reduces to the corresponding classical statistical method.  Tests of correlation coefficient between interview scores and academic scores from a sample of 30 applicants for admission to a college are considered to demonstrate the interpretation of test of correlation coefficient with fuzzy data in real-world situations.
机译:测试假设在推理统计中是重要的。与模糊环境相关的延伸非常有趣。这项工作的目的是阐明关于与模糊数据相关系数的假设的测试。首先以各种α值导出模糊样品相关系数的α-切割。然后基于这些α切割构建模糊测试统计的隶属函数。然后使用该隶属函数确定拒绝缺零假设的模糊概率。对于清晰的数据,此方法降低到相应的经典统计方法。从30名申请人入场商的采访分数和学术分数之间的相关系数被认为是展示了在现实世界情况下用模糊数据的相关系数试验的解释。

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