This chapter provides an overview of the various types of data used in statistical analysis, which anyone working with data in research or applied projects should know about. It distinguishes between qualitative (categorical) and quantitative (numerical) data, explaining how each type serves different purposes in research. The chapter further breaks down qualitative data into nominal and ordinal categories and quantitative data into discrete and continuous subtypes. These classifications help clarify how data can be categorised, measured, and analysed. In addition to these core data types, the chapter introduces the important concept of the cohort, which play a key role in longitudinal studies, allowing researchers to track groups with common characteristics over time. It also explains the difference between longitudinal and cross-sectional data, highlighting how data can be collected over time or at a single point. Finally, it discusses binary and dichotomous data.