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    Cluster Sampling

    Cluster sampling divides the population into naturally occurring groups (clusters) and randomly selects entire clusters, then surveys all or some members within them.

    Cluster sampling is used when a full sampling frame is impractical or expensive — e.g., surveying schools, hospitals, or franchise locations. Instead of randomly selecting individuals across the entire population, you randomly select clusters (a school district, a region, a store) and then survey within. Single-stage cluster sampling surveys everyone in selected clusters; two-stage adds a second random draw inside each. Cluster sampling is cheaper than random sampling but has higher design effect — effective sample size shrinks because units within a cluster are correlated.

    Example

    A retail chain with 500 stores can't survey every customer. They randomly select 25 stores and survey 40 customers in each, giving n = 1,000. Variance is higher than simple random sampling of 1,000 customers across all stores, so they apply a design-effect adjustment (typically 1.5×-3×) when reporting margin of error.

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    Related terms

    Random Sampling

    Random sampling is a probability sampling method where every member of the target population has an equal, known chance of being selected.

    Stratified Sampling

    Stratified sampling divides the population into mutually exclusive subgroups (strata) and samples randomly within each, ensuring proportional or oversampled representation.

    Convenience Sampling

    Convenience sampling recruits whoever is easiest to reach — website visitors, email-list subscribers, social-media followers — and is the dominant approach in commercial surveys despite its limitations.

    Sample Size

    Sample size is the number of respondents needed for survey results to be statistically meaningful at a given confidence level and margin of error.

    Margin of Error

    Margin of error is the range within which the true population value likely falls, given the sample size and confidence level.

    Confidence Interval

    A confidence interval is the range within which a true population parameter is expected to fall, at a specified confidence level.