Assessing normality for data with different sample sizes using SAS, Minitab and R
Different statistical packages may produce different results of statistical analysis such as normality test. One of possible sources of the difference is the computational approach. This study tries to explore results of normality tests based on different statistical packages. Empirical data with va...
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Asian Research Publishing Network
2016
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Online Access: | http://psasir.upm.edu.my/id/eprint/55127/1/Assessing%20normality%20for%20data%20with%20different%20sample%20sizes%20using%20SAS%2C%20Minitab%20and%20R.pdf http://psasir.upm.edu.my/id/eprint/55127/ http://www.arpnjournals.com |
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my.upm.eprints.551272018-08-13T08:02:41Z http://psasir.upm.edu.my/id/eprint/55127/ Assessing normality for data with different sample sizes using SAS, Minitab and R Fitrianto, Anwar Low, Yen Chin Different statistical packages may produce different results of statistical analysis such as normality test. One of possible sources of the difference is the computational approach. This study tries to explore results of normality tests based on different statistical packages. Empirical data with varied sample sizes were conducted. It was found that SAS, Minitab, and R produced different conclusion in normality test. Meanwhile, sample size also has effect on the test of normality where larger sample size tends to produce different conclusion of normality. But, all the three statistical packages produced similar results of normality test for AD and KS tests. Asian Research Publishing Network 2016-09 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/55127/1/Assessing%20normality%20for%20data%20with%20different%20sample%20sizes%20using%20SAS%2C%20Minitab%20and%20R.pdf Fitrianto, Anwar and Low, Yen Chin (2016) Assessing normality for data with different sample sizes using SAS, Minitab and R. ARPN Journal of Engineering and Applied Sciences, 11 (18). pp. 10845-10850. ISSN 1819-6608 http://www.arpnjournals.com |
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Different statistical packages may produce different results of statistical analysis such as normality test. One of possible sources of the difference is the computational approach. This study tries to explore results of normality tests based on different statistical packages. Empirical data with varied sample sizes were conducted. It was found that SAS, Minitab, and R produced different conclusion in normality test. Meanwhile, sample size also has effect on the test of normality where larger sample size tends to produce different conclusion of normality. But, all the three statistical packages produced similar results of normality test for AD and KS tests. |
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Fitrianto, Anwar Low, Yen Chin |
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Fitrianto, Anwar Low, Yen Chin Assessing normality for data with different sample sizes using SAS, Minitab and R |
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Fitrianto, Anwar Low, Yen Chin |
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Fitrianto, Anwar |
title |
Assessing normality for data with different sample sizes using SAS, Minitab and R |
title_short |
Assessing normality for data with different sample sizes using SAS, Minitab and R |
title_full |
Assessing normality for data with different sample sizes using SAS, Minitab and R |
title_fullStr |
Assessing normality for data with different sample sizes using SAS, Minitab and R |
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Assessing normality for data with different sample sizes using SAS, Minitab and R |
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assessing normality for data with different sample sizes using sas, minitab and r |
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Asian Research Publishing Network |
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2016 |
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http://psasir.upm.edu.my/id/eprint/55127/1/Assessing%20normality%20for%20data%20with%20different%20sample%20sizes%20using%20SAS%2C%20Minitab%20and%20R.pdf http://psasir.upm.edu.my/id/eprint/55127/ http://www.arpnjournals.com |
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