In social work research, measurement plays a crucial role in collecting, analyzing, and interpreting data related to social problems, human behaviour, and intervention outcomes. Levels of measurement refer to the ways in which variables are measured and classified in research. These levels determine the type of statistical analysis that can be applied and influence the accuracy and reliability of research findings. In social work research, understanding measurement levels is essential because it helps researchers choose appropriate tools for data collection and ensures meaningful interpretation of social phenomena. The first level of measurement is the nominal level of measurement. This is the most basic form of measurement where data are categorized without any quantitative value or ranking. In nominal measurement, variables are assigned to distinct groups or classes based on qualitative characteristics. Examples include classifying respondents by gender, religion, marital status, occupation, or type of social service received. In social work research, nominal measurement is commonly used to describe demographic characteristics of populations such as vulnerable groups, community categories, or service utilization patterns. The main purpose of nominal measurement is identification and classification rather than comparison of magnitude. Statistical techniques suitable for nominal data include mode, frequency distribution, and chi-square tests. However, nominal measurement does not allow researchers to determine order or distance between categories. The ordinal level of measurement is the next level, which provides ranking or ordering of variables based on a certain characteristic. In this level, data can be arranged in a meaningful sequence such as highest to lowest, most to least, or first to last. Although ordinal