![]() ![]() ![]() That means every member of the population can be clearly classified into exactly one subgroup. To use stratified sampling, you need to be able to divide your population into mutually exclusive and exhaustive subgroups. Frequently asked questions about stratified sampling.Step 4: Randomly sample from each stratum.Step 3: Decide on the sample size for each stratum. ![]() Step 2: Separate the population into strata.Step 1: Define your population and subgroups.This helps with the generalizability and validity of the study, as well as avoiding research biases like undercoverage bias. Researchers rely on stratified sampling when a population’s characteristics are diverse and they want to ensure that every characteristic is properly represented in the sample. Every member of the population studied should be in exactly one stratum.Įach stratum is then sampled using another probability sampling method, such as cluster sampling or simple random sampling, allowing researchers to estimate statistical measures for each sub-population. In a stratified sample, researchers divide a population into homogeneous subpopulations called strata (the plural of stratum) based on specific characteristics (e.g., race, gender identity, location, etc.). Try for free Stratified Sampling | Definition, Guide & Examples non-probability samplingĮliminate grammar errors and improve your writing with our free AI-powered grammar checker. ![]()
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