klusterinäytteenotto

Klusterinäytteenotto, or cluster sampling in English, is a probability sampling technique used in statistical surveys. It involves dividing the population into groups called clusters, and then randomly selecting a subset of these clusters for the sample. Once the clusters are selected, all individuals within those chosen clusters are included in the sample, or a further sampling method might be applied within the selected clusters. This approach is often employed when it is impractical or too expensive to obtain a simple random sample of individuals from a large, geographically dispersed population. For example, a researcher might divide a country into states (clusters), randomly select several states, and then survey all households within those selected states. The primary advantage of cluster sampling is its cost-effectiveness and efficiency compared to other probability sampling methods, especially when the population is spread out. However, it can also lead to a higher sampling error if the clusters are not representative of the entire population, meaning there's a risk that the individuals within a cluster are more similar to each other than to individuals in other clusters. Careful consideration of cluster definition and selection is crucial for ensuring the validity of the results.