Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-9473(03)00009-4
Title: Using normal quantile plot to select an appropriate transformation to achieve normality
Authors: Tan, W.D.
Gan, F.F. 
Chang, T.C.
Keywords: Box-Cox transformation
Exploratory data analysis
Exponential transformation
Graphical methods
Robust estimation
Symmetry
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

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

12
checked on Jan 18, 2022

WEB OF SCIENCETM
Citations

13
checked on Jan 18, 2022

Page view(s)

101
checked on Jan 20, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.