Which sampling technique ensures that each individual has an equal chance of being selected?

Simple random sampling is a technique where every individual in a population has an equal probability of being selected for the sample. This method is often perceived as the most straightforward and unbiased way to gather data because it reduces the risk of selection bias. In this process, each member of the population is listed, and selections are made often via random number generators or drawing lots, ensuring that every individual has the same likelihood of inclusion.

In contrast, systematic sampling involves selecting individuals based on a fixed interval from a randomly selected starting point, which can inadvertently introduce bias if there are patterns in the data. Stratified sampling involves dividing the population into homogeneous subgroups before random sampling each subgroup, ensuring representation but not equal chances across all individuals. Cluster sampling divides the population into clusters, then randomly selects some of those clusters and surveys all or a random sample of individuals from those clusters. While each method has its own strengths in facilitating diverse or representative samples, only simple random sampling guarantees equal chances for each individual selected.