Collecting information from every individual in a population can be both time-intensive and costly. Sampling offers a practical and efficient alternative by allowing researchers to study a representative subset of a population and use the findings to draw reliable conclusions about the whole. Through statistical techniques, sample data can be used to estimate population characteristics, such as averages, proportions, and relationships between variables. Sampling plays a vital role in generating the information needed to understand economic, social, and scientific phenomena. It provides a robust foundation for estimating unknown values, evaluating trends, and testing hypotheses, while ensuring that data collection efforts remain cost-effective and manageable. By focusing resources on a carefully selected sample, organizations can achieve high-quality results without the need for a full population census. A key advantage of probability sampling is its ability to produce not only accurate estimates but also measures of their precision, such as margins of error. This enables researchers and decision-makers to assess the reliability of their findings and supports the widespread use of probability sampling as a trusted and objective tool for statistical analysis. The ILO Department of Research and Statistics, in collaboration with the ITCILO, is proud to offer the online course "Sampling Design and Weighting", designed to equip participants with the knowledge and practical skills needed to develop effective sampling strategies and produce reliable statistical estimates.