How is stratified sampling conducted?

Stratified sampling is a technique used to ensure that different segments of a population are adequately represented in a sample. This method begins with dividing the entire population into distinct subgroups, or strata, that share similar characteristics. After these strata are defined, samples are then randomly selected from each subgroup. This approach is particularly beneficial because it helps to reduce sampling bias and increases the precision of the overall sample.

By utilizing stratified sampling, researchers can also ensure that important subgroups are not overlooked, which could be a limitation in other sampling methods. For example, if a population includes various age groups, income levels, or geographic locations, stratified sampling ensures that each of these segments is sampled appropriately according to its proportion in the total population, allowing for more accurate generalizations about the entire population based on the sample findings. This structured methodology enhances the reliability of the data collected.