Final answer:
Stratified sampling involves dividing the population into distinct groups called strata and taking random samples from each stratum. Cluster sampling involves dividing the population into clusters or groups and randomly selecting some clusters. Multistage sampling is a combination of stratified and cluster sampling, where the population is divided into clusters and then samples are taken from each stratum within each cluster.
Step-by-step explanation:
There are several types of probability samples:
- Stratified sample: In this type of sample, the population is divided into distinct groups called strata based on certain characteristics. Then, random samples are taken from each stratum. For example, in a study on a school, the population can be divided into strata such as grade levels or genders, and a sample is taken from each stratum.
- Cluster sample: In this type of sample, the population is divided into clusters or groups, and some clusters are randomly selected. All members of the selected clusters are included in the sample. For example, in a study on a city, the population can be divided into geographical regions, and some regions are randomly selected for the sample.
- Multistage sample: This is a combination of stratified and cluster sampling. The population is divided into clusters, and then within each cluster, strata are defined, and samples are taken from each stratum.