Data Analysis Concepts refer to the theoretical and methodological principles, techniques, and procedures that underpin the systematic process of inspecting, cleansing, transforming, and modelling data in social research with the goal of discovering useful information, informing conclusions, and supporting decision-making. This category encompasses various statistical measures, including measures of central tendency (like mean, median, mode) and measures of dispersion (like range, standard deviation, interquartile range), which summarise and describe the distribution of data. It also includes concepts related to understanding relationships between variables, such as correlation (the degree to which variables vary together) and causation (where one variable directly influences another), as well as the logical reasoning (causal logic) behind establishing such relationships. Furthermore, it covers key aspects of measurement quality, including the operational definition of concepts, and principles that ensure the reliability (consistency) and validity (accuracy) of data analysis, as well as specific metrics like incidence and prevalence in demographic or epidemiological studies. These concepts are crucial for interpreting empirical material, testing hypotheses, and drawing valid and reliable conclusions about social phenomena in sociological inquiry.