• Farrokh Habibzadeh.
• Past President, World Association of Medical Editors (WAME), Editorial Consultant, The Lancet, Associate Editor, Frontiers in Epidemiology. Farrokh.Habibzadeh@gmail.com.
• J. Korean Med. Sci. 2024 Jan 22; 39 (3): e35e35.

AbstractDetermining if the frequency distribution of a given data set follows a normal distribution or not is among the first steps of data analysis. Visual examination of the data, commonly by Q-Q plot, although is acceptable by many scientists, is considered subjective and not acceptable by other researchers. One-sample Kolmogorov-Smirnov test with Lilliefors correction (for a sample size ≥ 50) and Shapiro-Wilk test (for a sample size < 50) are common statistical tests for checking the normality of a data set quantitatively. As parametric tests, which assume that the data distribution is normal (Gaussian, bell-shaped), are more robust compared to their non-parametric counterparts, we commonly use transformations (e.g., log-transformation, Box-Cox transformation, etc.) to make the frequency distribution of non-normally distributed data close to a normal distribution. Herein, I wish to reflect on presenting how to practically work with these statistical methods through examining of real data sets.© 2024 The Korean Academy of Medical Sciences.

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