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	क्लस्टर सैंपलिंग (Cluster Sampling)	डबल सैंपलिंग
क्षेत्र	सर्वेक्षण पद्धति	प्रतिचयन
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	Early-to-mid 20th century; canonical treatment 1953/1977	1938
प्रवर्तक	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice	Jerzy Neyman
प्रकार	Probability sampling design	Multi-phase sampling design
मौलिक स्रोत	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407	Neyman, J. (1938). Contribution to the theory of sampling human populations. Journal of the American Statistical Association, 33(201), 101–116.
उपनाम	cluster random sampling, area sampling, one-stage cluster sampling	Two-Phase Sampling
संबंधित	5	4
सारांश	Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters.	Double Sampling (also called two-phase or multistage sampling) is a survey design in which a large preliminary sample is collected using inexpensive methods or partial information, then a smaller subsample is drawn from it and measured in detail. Pioneered by Jerzy Neyman in 1938, it is particularly useful when a cheap surrogate measurement is available but true measurement is expensive.