Change search
ReferencesLink to record
Permanent link

Direct link
Generation of Non-normalData: A Study ofFleishman’s PowerMethod
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2011 (English)Report (Other academic)
Abstract [en]

Fleishman's power method is one of the traditional methods used for generatingnon-normal random numbers. In this paper, we use Monte Carlo simulationto test the reliability of this method. Specially, we assess the performance of the method under different conditions of skewness, kurtosis and sample sizes.The power of the normality test statistics proposed by D'Agostino (1986) isstudied based on the generated samples. The results suggest that Fleishman'smethod has difficulties on generating non-normal samples with higher levels of skewness and kurtosis. The effect of sample size is found to be significant on the reliability of the data generation. The parabola, which indicates the bottomboundary of the possible combination of skewness and kurtosis calculated by Fleishman (1978), is shown to be incorrect. When it comes to the power study, a considerable impact of sample size is also observed on obtaining a trustworthytest decision based on the generated non-normal samples.

Place, publisher, year, edition, pages
Uppsala: Department of Statistics, Uppsala University , 2011. , 29 p.
Series
Working paper / Department of Statistics, Uppsala University, 2011:1
Keyword [en]
non-normal data, Fleishman's method, D'Agostino test of normality, power of the test
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-150623OAI: oai:DiVA.org:uu-150623DiVA: diva2:407995
Available from: 2011-04-01 Created: 2011-04-01 Last updated: 2011-04-01Bibliographically approved

Open Access in DiVA

fulltext(702 kB)3208 downloads
File information
File name FULLTEXT01.pdfFile size 702 kBChecksum SHA-512
cc34a7989524065fdd3c369480ee52a9e6b4212b9c387a9ec615c75a361628a5e7ba6295a6b1c2d2fd1072d9b36b0668c4b43588710404edda4754cd10d3b748
Type fulltextMimetype application/pdf

By organisation
Department of Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 3208 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 236 hits
ReferencesLink to record
Permanent link

Direct link