Sampling with replacement is a statistical method where each item selected from a population is returned to the population before the next selection. This means that the same item can be chosen multiple times in the sampling process. It is often used in experiments and surveys to ensure that every item has an equal chance of being selected each time. This technique is important in various fields, including statistics, data analysis, and machine learning. By allowing repeated selections, sampling with replacement helps to create a more comprehensive understanding of the population's characteristics, leading to more reliable results in studies and analyses.