Klastriproovivõtus

Klastriproovivõtus, also known as cluster sampling, is a statistical sampling method used in research. It involves dividing a population into subgroups called clusters. These clusters are often geographical or organizational units. The researcher then randomly selects a certain number of these clusters. All individuals within the selected clusters are then included in the sample. This contrasts with simple random sampling where every individual has an equal chance of being selected.

The primary advantage of cluster sampling is its cost-effectiveness and efficiency, especially when dealing with large or geographically dispersed populations. It can significantly reduce the time and resources required for data collection compared to other methods. For instance, in a survey of a country, selecting a few cities (clusters) and surveying everyone within those cities might be more feasible than surveying individuals spread across the entire country.

However, cluster sampling can introduce sampling bias if the selected clusters are not representative of the entire population. The individuals within a cluster may share similar characteristics, leading to less diversity in the sample compared to a simple random sample. This can affect the accuracy of the estimates derived from the sample. Therefore, careful consideration of cluster selection and the potential for intracluster correlation is important when designing a study using this method.