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|Title:||Using normal quantile plot to select an appropriate transformation to achieve normality||Authors:||Tan, W.D.
Exploratory data analysis
|Issue Date:||10-Apr-2004||Citation:||Tan, W.D., Gan, F.F., Chang, T.C. (2004-04-10). Using normal quantile plot to select an appropriate transformation to achieve normality. Computational Statistics and Data Analysis 45 (3) : 609-619. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-9473(03)00009-4||Abstract:||The normal quantile plot is a popular and useful tool for assessing the normality of a data set. A nonlinear plot is used to infer evidence that the data did not come from a normal population. The curvature of a plot is exploited to suggest a transformation required to normalize the data, if it exists. This is done by comparing the curvature of a plot against a series of reference curves which correspond to different transformations. Unlike the maximum likelihood method, this technique is robust to outliers. © 2003 Elsevier B.V. All rights reserved.||Source Title:||Computational Statistics and Data Analysis||URI:||http://scholarbank.nus.edu.sg/handle/10635/105455||ISSN:||01679473||DOI:||10.1016/S0167-9473(03)00009-4|
|Appears in Collections:||Staff Publications|
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