Gathering information about the characteristics of a population for each of its members is time consuming and costly. However, we can make inferences about the population with the help of samples. Sampling is a statistical procedure that is concerned with the collection of data on a part of a population of interest and subsequent extrapolation to make statistical inferences about the whole population, for example using sample means to estimate population means. Sampling is essential to enable collection the vast amount of information required for understanding the functioning of our society. It provides a solid basis for estimating unknown values and ratios, and for testing the validity of presumed relationships in different areas of science. At the same time, it is crucial in assuring the efficient use of scarce resources for data collection, while maintaining data quality. One important aspect of probability sampling is its ability to produce not only valid estimates of the parameters of interest but also, under broad conditions, of their margin of errors due to sample variability. This feature has no doubt greatly contributed to the wide acceptance of probability sampling as an objective tool of measurement among analysts and the public at large. The ILO Department of Statistics, in collaboration with the ITCILO, is proud to offer the online course "Sampling Design and Weighting".