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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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/ |
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Local University |
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Universiti Kebangasaan Malaysia |
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UKM Institutional Repository |
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Online Access |
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English |
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. |
format |
Article |
author |
Ani Shabri, Abdul Aziz Jemain, |
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 |
author_facet |
Ani Shabri, Abdul Aziz Jemain, |
author_sort |
Ani Shabri, |
title |
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_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_sort |
pengujian kesesuaian taburan normal berdasarkan statistik cramer-von mises = test of suitability of normal distribution based on cramer-von mises statistics |
publisher |
Universiti Kebangsaan Malaysia |
publishDate |
2007 |
url |
http://journalarticle.ukm.my/104/ http://journalarticle.ukm.my/104/ http://journalarticle.ukm.my/104/1/1.pdf |
first_indexed |
2023-09-18T19:00:59Z |
last_indexed |
2023-09-18T19:00:59Z |
_version_ |
1777403072176193536 |