Stratified sampling is a sampling method used in statistics to address this kind of situation, where the main group has significant subgroups of interest. Common variables used to define subgroups include age, gender, race, income, education level, or geographic location. The sampling technique involves dividing a population into subgroups, or
Stratified Sampling Definition. Stratified sampling is a random sampling method of dividing the population into various subgroups or strata and drawing a random sample from each. Each subgroup or stratum consists of items that have common characteristics. This sampling method is widely used in human research or political surveys.In a stratified sample, the population of N sampling units is divided into H exhaustive and mutually exclusive subpopulations, such that N1 + N2 + … + NH = N. Once the strata are determined, independent simple random samples are drawn from each strata, denoted by n1, n2, … , nH, respectively. The total sample size is denoted n. Stratified sampling is a technique that divides the population into groups, or strata, based on some common characteristic, such as gender, age, or income. Then, a random sample is drawn from each
For this reason, simple random sampling is more commonly used when the researcher knows little about the population. If the researcher knew more, it would be better to use a different sampling technique, such as stratified random sampling, which helps to account for the differences within the population, such as age, race or gender.In stratified sampling, the aim is to ensure that each subgroup (stratum) of the population is adequately represented within the sample. For instance, if researching gender differences, a researcher might use stratified sampling to ensure both male and female perspectives are represented equally. Furthermore, it was noted that stratified random sampling has the potential to significantly reduce the workload associated with data collecting, and reducing the amount of data collected makes it possible to pay more attention to the quality of the collected data. Strengths and Weaknesses of Stratified Sampling Strengths: GLIQ9E.