Descriptive statistics are essential in biomedical research for summarizing data features. They include measures of central tendency (mean, median, mode) and dispersion (variance, standard deviation, range, etc.). For continuous data, testing normality is crucial as it determines the choice of statistical methods. Normality tests, such as Shapiro-Wilk and Kolmogorov-Smirnov, help decide whether parametric or nonparametric tests are appropriate. Numerical and visual methods are used for normality testing, each with its own advantages and limitations. Descriptive statistics and normality tests are both vital in data analysis. The article discusses summary measures and normality tests, using an example dataset of 15 patients' mean arterial pressure (MAP) to illustrate concepts. Measures of central tendency include mean, median, and mode, while measures of dispersion include standard deviation, variance, and interquartile range. Normality testing involves statistical tests and graphical methods like histograms, box plots, Q-Q plots, and P-P plots. The Shapiro-Wilk test is preferred for small samples, while the Kolmogorov-Smirnov test is used for larger samples. The article emphasizes the importance of normality testing in determining appropriate statistical methods and highlights the use of descriptive statistics in biomedical research.Descriptive statistics are essential in biomedical research for summarizing data features. They include measures of central tendency (mean, median, mode) and dispersion (variance, standard deviation, range, etc.). For continuous data, testing normality is crucial as it determines the choice of statistical methods. Normality tests, such as Shapiro-Wilk and Kolmogorov-Smirnov, help decide whether parametric or nonparametric tests are appropriate. Numerical and visual methods are used for normality testing, each with its own advantages and limitations. Descriptive statistics and normality tests are both vital in data analysis. The article discusses summary measures and normality tests, using an example dataset of 15 patients' mean arterial pressure (MAP) to illustrate concepts. Measures of central tendency include mean, median, and mode, while measures of dispersion include standard deviation, variance, and interquartile range. Normality testing involves statistical tests and graphical methods like histograms, box plots, Q-Q plots, and P-P plots. The Shapiro-Wilk test is preferred for small samples, while the Kolmogorov-Smirnov test is used for larger samples. The article emphasizes the importance of normality testing in determining appropriate statistical methods and highlights the use of descriptive statistics in biomedical research.