Klusterinäytteenoton

Klusterinäytteenotto, or cluster sampling, is a probability sampling technique used in statistics. It involves dividing the population into groups called clusters, then randomly selecting a subset of these clusters. All individuals within the selected clusters are then included in the sample. This method is often employed when a complete list of all members of the population is unavailable or impractical to obtain.

The primary advantage of cluster sampling is its cost-effectiveness and efficiency, especially for geographically dispersed populations. Instead of sampling individuals across the entire population, researchers can focus their efforts on specific, randomly chosen areas or groups. This reduces travel time and administrative costs.

However, cluster sampling can also introduce sampling errors. If the clusters are not representative of the entire population, the sample may be biased. The variability within clusters is typically lower than the variability across the entire population, which can lead to underestimation of the true population variance. Therefore, careful consideration of cluster definition and selection is crucial for obtaining reliable results. This technique is commonly used in surveys for education, public health, and social sciences.