非正态分布连续数据的参数检验:正反

Electronic Physician Pub Date : 2019-02-25 DOI:10.19082/7468
Umesh Wadgave, M. Khairnar
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引用次数: 8

摘要

在分析非正态分布连续数据的参数和非参数统计检验之间进行选择是一个长期存在的争议。按照惯例,建议使用非参数测试,但很少有其他人建议使用参数测试。本文评价了在分析非正态分布连续数据时比较参数检验和非参数检验的模拟研究。只有当数据高度偏斜并且对数变换技术不能将其改变为正态分布时,才建议进行非参数测试。然而,在大多数其他情况下,参数测试在分析非正态分布连续数据方面更强大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parametric test for non-normally distributed continuous data: For and against
Choosing between parametric and non-parametric statistical tests for analysis of non-normally distributed continuous data is a long-standing controversy. Conventionally, it is recommended to use non-parametric tests but few others suggest using the parametric test. This article evaluates the simulation studies comparing the parametric tests with non-parametric tests in analysing the non-normally distributed continuous data. Nonparametric tests are recommended only when data is highly skewed and log transformation technique cannot change it to normal distribution. However, in most other situations parametric tests are more powerful in analysing non-normally distributed continuous data.
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