Random sampling is a probability sampling method in which every member of the defined population has a known and usually equal chance of being selected for inclusion in a study. It is an important method in public health and epidemiological research because it helps researchers obtain a sample that represents the target population and reduces selection bias. Random sampling is particularly useful when studying disease prevalence, risk factors, health behaviours, mortality, morbidity and the utilization of health services. In epidemiology, the population of interest may consist of all individuals living in a particular geographical area, all children of a certain age group, or all patients attending specified health facilities. Since it is often impractical or impossible to study the entire population, a representative sample is selected. Random sampling ensures that selection is based on chance rather than on the investigator's preference. A sampling frame, such as a population register, electoral list, household list or health-service register, is generally required. In simple random sampling, each individual in the sampling frame has an equal probability of selection. Selection can be carried out using a lottery method, random number table, computer-generated random numbers or other suitable randomization techniques. For example, if an epidemiologist wants to study the prevalence of hypertension among 10,000 adults and needs a sample of 500, each adult