Salīdzināt metodes

	Klasteru izlase	Divu pakāpju izlase
Nozare	Aptauju metodoloģija	Izlases veidošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	Early-to-mid 20th century; canonical treatment 1953/1977	1938
Autors	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice	Jerzy Neyman
Tips	Probability sampling design	Multi-phase sampling design
Pirmavots	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.
Citi nosaukumi	cluster random sampling, area sampling, one-stage cluster sampling	Two-Phase Sampling
Saistītās	5	4
Kopsavilkums	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.