Statistics Notes: Transforming data
Statistics Notes: Transforming data
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统计笔记：转换数据
DOI：
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发表时间：
1996
期刊：
影响因子：
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通讯作者：
D. Altman
中科院分区：
文献类型：
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作者：
M. Bland;D. Altman
我们经常通过取对数、平方根、倒数或数据的其他函数来转换数据。然后，我们分析转换后的数据，而不是未转换的数据或原始数据。我们这样做是因为许多统计技术，如t检验，回归和方差分析，要求数据遵循特定类型的分布。观测值本身必须来自服从正态分布的总体，1不同的观测值组必须来自具有相同方差或标准差的总体。我们需要这种均匀的方差，因为我们估计组内的方差，并且只有当我们可以假设每个组中的方差相同时，我们才能做得很好。许多生物变量确实遵循具有均匀方差的正态分布。许多不这样做的人可以通过适当的转换来这样做。幸运的是，使数据遵循正态分布的转换...
We often transform data by taking the logarithm, square root, reciprocal, or some other function of the data. We then analyse the transformed data rather than the untransformed or raw data. We do this because many statistical techniques, such as t tests, regression, and analysis of variance, require that data follow a distribution of a particular kind. The observations themselves must come from a population which follows a normal distribution,1 and different groups of observations must come from populations which have the same variance or standard deviation. We need this uniform variance because we estimate the variance within the groups, and we can do this well only if we can assume it to be the same in each group. Many biological variables do follow a normal distribution with uniform variance. Many of those which do not can be made to do so by a suitable transformation. Fortunately, a transformation which makes data follow a normal distribution …