# Types of Probability Sampling

Cluster Sampling

Cluster sampling is a sampling technique in which clusters of participants that represent the population are identified and included in the sample

Multistage Sampling

Three examples of probability sampling include: cluster sampling, which involves randomly choosing clusters, or natural divisions; multistage sampling, which involves randomly choosing a sample from each cluster; and multiphase sampling, which involves gathering data from a large sample and then gathering additional data from a smaller sub-sample.

source: study.com
Simple Random Sampling (SRS)

A simple random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. An example of a simple random sample would be the names of 25 employees being chosen out of a hat from a company of 250 employees.

Stratified Sampling

Stratified sampling is a probability sampling technique wherein the researcher divides the entire population into different subgroups or strata, then randomly selects the final subjects proportionally from the different strata.

Systematic Sampling

Systematic sampling is a probability sampling method in which a random sample from a larger population is selected.