The empirical cumulative average deviation function introduced by the author is utilized to develop both Ad- and Ud-plots. The Ad-plot can identify symmetry, skewness, and outliers of the data distribution, including anomalies. The Ud-plot created by slightly modifying Ad-plot is exceptional in assessing normality, outperforming normal QQ-plot, normal PP-plot, and their derivations. The d-value that quantifies the degree of proximity between the Ud-plot and the graph of the estimated normal density function helps guide to make decisions on confirmation of normality. Full description of this methodology can be found in the article by Wijesuriya (2025) <doi:10.1080/03610926.2024.2440583>.
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