All members of the population should be in only one stratum. For example, if your research question requires you to compare outcomes between income levels, you might base the strata on income. Researchers can create strata based on income, gender, and race, among many other possibilities. Strata are subpopulations whose members are relatively similar to each other compared to the broader population. When researchers use non-random selection to choose subjects from the strata, it is known as Quota Sampling. Then, they draw a random sample from each group (stratum) and combine them to form their complete representative sample. The stratified sampling process starts with researchers dividing a diverse population into relatively homogeneous groups called strata, the plural of stratum. This technique is a probability sampling method, and it is also known as stratified random sampling. Many surveys use this method to understand differences between subpopulations better. It also helps them obtain precise estimates of each group’s characteristics. Researchers use stratified sampling to ensure specific subgroups are present in their sample. Stratified sampling is a method of obtaining a representative sample from a population that researchers have divided into relatively similar subpopulations (strata).
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