Abstract
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.
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Vaclavik, M., Sikorova, Z., Barot, T. (2020). Skewness in Applied Analysis of Normality. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Software Engineering Perspectives in Intelligent Systems. CoMeSySo 2020. Advances in Intelligent Systems and Computing, vol 1295. Springer, Cham. https://doi.org/10.1007/978-3-030-63319-6_86
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