Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics

Since normal distributions are the most important ones in statistics, there are large number of tests for normality. However they have less some drawbacks. Some of these tests are simple but suitable for some situations. In this study, the traditional Cramer-von Mises test statistics is modified ba...

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Main Authors: Ani Shabri, Abdul Aziz Jemain
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2007
Online Access:http://journalarticle.ukm.my/104/
http://journalarticle.ukm.my/104/1/1.pdf
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author Ani Shabri,
Abdul Aziz Jemain,
author_facet Ani Shabri,
Abdul Aziz Jemain,
author_sort Ani Shabri,
building UKM Institutional Repository
collection Online Access
description Since normal distributions are the most important ones in statistics, there are large number of tests for normality. However they have less some drawbacks. Some of these tests are simple but suitable for some situations. In this study, the traditional Cramer-von Mises test statistics is modified based on Weibull formula. The new goodness-of-fit test is compared with the traditional Anderson-Darling (AD), Cramer von-Mises (CR), Kolmogorov-Smirnov (KS) and Shapiro-Wilk (SW) test statistics. A simulation study using several different distributions shows that the proposed test is very powerful for testing normality.
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format Article
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institution Universiti Kebangasaan Malaysia
institution_category Local University
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publisher Universiti Kebangsaan Malaysia
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spelling ukm-1042016-12-14T06:26:25Z http://journalarticle.ukm.my/104/ Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics Ani Shabri, Abdul Aziz Jemain, Since normal distributions are the most important ones in statistics, there are large number of tests for normality. However they have less some drawbacks. Some of these tests are simple but suitable for some situations. In this study, the traditional Cramer-von Mises test statistics is modified based on Weibull formula. The new goodness-of-fit test is compared with the traditional Anderson-Darling (AD), Cramer von-Mises (CR), Kolmogorov-Smirnov (KS) and Shapiro-Wilk (SW) test statistics. A simulation study using several different distributions shows that the proposed test is very powerful for testing normality. Universiti Kebangsaan Malaysia 2007-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/104/1/1.pdf Ani Shabri, and Abdul Aziz Jemain, (2007) Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics. Sains Malaysiana, 36 (2). pp. 201-206. ISSN 0126-6039 http://www.ukm.my/jsm/
spellingShingle Ani Shabri,
Abdul Aziz Jemain,
Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics
title Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics
title_full Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics
title_fullStr Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics
title_full_unstemmed Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics
title_short Pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = Test of suitability of normal distribution based on cramer-von mises statistics
title_sort pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = test of suitability of normal distribution based on cramer-von mises statistics
url http://journalarticle.ukm.my/104/
http://journalarticle.ukm.my/104/
http://journalarticle.ukm.my/104/1/1.pdf