This chapter covers descriptive statistics, the branch of statistics that summarises and presents data in a meaningful way. It outlines key measures of central tendency, including mean, median, and mode, and measures of dispersion such as range, variance, and standard deviation. Graphical methods, including histograms, boxplots, and scatterplots, are described as tools for visualising data distributions and relationships. The chapter highlights the role of descriptive statistics in providing initial insights into data, detecting patterns, and identifying potential anomalies. The importance of choosing appropriate measures based on data type and distribution is emphasised. Limitations of descriptive statistics are acknowledged, particularly their inability to draw conclusions beyond the data set or establish causality. Practical examples are provided, demonstrating how descriptive methods are used in summarising patient characteristics, reporting disease prevalence, and monitoring health service activity. The chapter concludes by positioning descriptive statistics as the foundation upon which more advanced inferential methods are built. This chapter maps to syllabus section 2.1–2.2, which require knowledge of descriptive data presentation, measures of central tendency and dispersion, and graphical methods.