Key concepts

Cluster sampling is a sampling technique used when "natural" but relatively homogeneous groupings are evident in a statistical population. It is often used in marketing research.

Cluster sampling refers to a sampling method that has the following properties.

• The population is divided into N groups, called clusters.
• The researcher randomly selects n clusters to include in the sample.
• The number of observations within each cluster M_i is known, and M = M₁ + M₂ + M₃ + ... + M_N-1 + M_N.
• Each element of the population can be assigned to one, and only one, cluster.

This tutorial covers two types of cluster sampling methods.

• One-stage sampling. All of the elements within selected clusters are included in the sample.
• Two-stage sampling. A subset of elements within selected clusters are randomly selected for inclusion in the sample.