Skewness in Applied Analysis of Normality
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17450%2F20%3AA210276O" target="_blank" >RIV/61988987:17450/20:A210276O - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-63319-6_86" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-63319-6_86</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-63319-6_86" target="_blank" >10.1007/978-3-030-63319-6_86</a>
Alternative languages
Result language
angličtina
Original language name
Skewness in Applied Analysis of Normality
Original language description
In the quantitative research, the property of the normality of data is an important assumption. For the particular selection of the concrete statistical methods, e.g. for purposes of the testing the hypotheses, the knowledge of the normality of data has the significant role. There exists a wide spectrum of methods aimed for the purposes of the testing the normality. These tests are based on the consideration of the statistical significance level. In this paper, a descriptive approach to an analysis of the normality is realized with regards to the sample parameter of the skewness. This parameter is explored with a consideration of the changing sample size in the frame of the applied quantitative research with 2671 respondents. The shapes of the histograms are discussed in a context of the obtained results of the parameter of the skewness. The trend of the dependence of the skewness on the Shapiro-Wilk criterion is analyzed using the regression analysis.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Software Engineering Perspectives in Intelligent Systems (vol.2), Advances in Intelligent Systems and Computing (vol. 1295)
ISBN
978-3-030-63318-9
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
11
Pages from-to
927-937
Publisher name
Springer Nature
Place of publication
Cham
Event location
Zlin
Event date
Oct 14, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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