A random sample is a subset of a population in which every member has an equal chance of being selected. The goal is to produce a group that fairly represents the larger population from which it is drawn.

Simple random sampling gives each individual the same probability of inclusion. Stratified sampling first divides the population into subgroups and then samples randomly within each, ensuring representation of important categories. Random sampling reduces selection bias and supports statistical generalization from the sample to the population. In practice, truly random samples are difficult to obtain; many studies rely on convenience samples and note the resulting limits on generalizability.

Sample size also matters. Larger random samples produce more stable estimates and narrower confidence intervals. Polling organizations and survey researchers invest considerable effort in constructing sampling frames and minimizing nonresponse so that the final sample remains close to random.

When every member of the population has the same chance of appearing in the study, the sample is random.