IID Sampling

IID sampling, which stands for "independent and identically distributed" sampling, refers to selecting data points from a population where each sample is chosen randomly and independently of others, following the same probability distribution. This means each sample has the same chance of being selected and does not influence or depend on previous samples. IID sampling is fundamental in statistics and machine learning because it ensures that collected data accurately reflects the overall population and allows for reliable analysis, modeling, and inference without bias introduced by dependence or varying probabilities.