In research, obtaining a representative sample is vital for ensuring that the data collected accurately reflects the characteristics of the larger population being studied. A representative sample is a subset of a population that mirrors the important characteristics of the entire group, enabling researchers to make accurate generalizations and predictions about the population as a whole.
To choose a representative sample, researchers employ various sampling techniques, including simple random sampling, stratified sampling, and cluster sampling. Simple random sampling involves selecting individuals from the population entirely at random, giving each member an equal chance of being included. Stratified sampling divides the population into subgroups (strata) based on specific characteristics and then randomly selects individuals from each stratum. Cluster sampling divides the population into clusters and randomly selects a few clusters to represent the entire population.