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A SAS program to assess the sensitivity of normality tests on non-normal data

Sin, Yin Teh and Ahad, Nor Aishah and Othman, Abdul Rahman (2013) A SAS program to assess the sensitivity of normality tests on non-normal data. In: 20th National Symposium on Mathematical Sciences, 18–20 December 2012, Palm Garden Hotel, Putrajaya, Malaysia.

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Abstract

In many statistical analyses, the data is usually assumed to be approximately normal or normally distributed. Unfortunately, not all data can be assumed normal in real life.To assess the normality of the data, there are four statistical tests, i.e. the Kolmogorov-Smirnov test, the Anderson-Darling test, the Cramer-von Mises test, and the Shapiro-Wilk test that are extensively used by practitioners.The general purpose of this article is to provide a demonstration of Base SAS programming codes of DATA STEP, PROC UNIVARIATE, PROC MEANS and SAS functions to evaluate the performance of the above mentioned tests, under various spectrums of non-normal distributions and different sample sizes.Another important goal is to help researchers adapt these codes to perform similar analyses for other non-normal distributions or other normality tests.This is to encourage the researchers to check the sensitivity of the normality tests before they implement any test that requires assumption of normality.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN: 978-0-7354-1150-0
Uncontrolled Keywords: Researchers .Statistical analysis.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Quantitative Sciences
Depositing User: Mrs. Nor Aishah Ahad
Date Deposited: 09 Nov 2016 09:10
Last Modified: 09 Nov 2016 09:10
URI: https://repo.uum.edu.my/id/eprint/19062

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