生物测定中的数据转换

Sylvio Péllico Netto, A. Behling
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引用次数: 0

摘要

方差分析是最常用于同时比较三个或多个平均值的统计检验。然而,它的应用需要遵守一些假设,主要强调数据的正态性和方差的均方差。当不满足这些要求时,另一种选择是进行数据转换,以使实验评估具有连续性。随着Tukey的数据转换系统的提出,被理解为一个功率转换系统,即对数据集(X⅟n)的n次方根的应用,这个统计过程在方法上得到了发展,以确保这样的解决方案。在目前的研究中,我们提出了对这个系统的补充,在这里命名为四个步骤的转换,包括两个假设检验来评估正态性和同方差。将该方法应用于实验数据,评价了野生金合欢林分土壤水平的有效辐射量。我们提出了一种数据转换模型,以同时获得同方差和正态性。该方法适合确保实验数据的这两个统计方面,允许通过常规方差分析对八种处理进行比较。指标项:方差分析、均方差分析、正态性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data transformation in biological assays
The analysis of variance is the statistical test most used for comparison of three or more means simultaneously. Its application requires, however, the compliance to some assumptions, with main emphasis on normality of the data and homoscedasticity of variances. When such requirements are not met, one of the alternatives is the data transformation to enable the continuity of the experimental evaluation. With the proposition of the Tukey’s data transformation system, understood as a power transformation system, i.e. the application of nth root on a data set (X⅟n) this statistical procedure has methodologically evolved to ensure such solutions. In the present research we proposed a complement to this system, denominated here as transformation in four steps, with inclusion of two hypothesis tests to evaluate normality and homoscedasticity. This was applied on experimental data to evaluate the amount of radiation available at soil level within stands of Acacia mearnsii De Wild. We have proposed a model for data transformation to simultaneously obtain homoscedasticity and normality. The methodology was appropriate to ensure these two statistical aspects on the experimental data, allowing comparison of eight treatments by conventional analysis of variance. Index terms: Analysis of variance, homoscedasticity, normality.
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