What is stratified, quota, cluster and multistage sampling?

1. Stratified sampling: In stratified sampling, the population is divided into subgroups or strata based on certain characteristics that are important to the research. Samples are then randomly selected from each stratum in proportion to their size in the population. This method ensures that each subgroup is represented in the sample, making it more representative of the population as a whole.

2. Quota sampling: Quota sampling is a non-probability sampling method where researchers divide the population into subgroups based on certain characteristics and then set quotas for each subgroup. Researchers then select participants from each subgroup until the quota is filled. Quota sampling is often used in market research and opinion polls.

3. Cluster sampling: In cluster sampling, the population is divided into clusters or groups, and a random sample of clusters is selected. All individuals within the selected clusters are then included in the sample. This method is often used when it is difficult or impractical to obtain a complete list of the population, such as in large geographical areas.

4. Multistage sampling: Multistage sampling is a complex sampling method that involves multiple stages of sampling. In this method, the population is divided into clusters, and then clusters are further divided into subclusters. Samples are then selected at each stage until the final sample is obtained. Multistage sampling is often used in large-scale surveys and studies.