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| Cluster Sampling× | Kettős mintavétel× | |
|---|---|---|
| Tudományterület≠ | Kérdőíves felmérések módszertana | Mintavétel |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | Early-to-mid 20th century; canonical treatment 1953/1977 | 1938 |
| Megalkotó≠ | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice | Jerzy Neyman |
| Típus≠ | Probability sampling design | Multi-phase sampling design |
| Alapmű≠ | 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. DOI ↗ |
| Alternatív nevek≠ | cluster random sampling, area sampling, one-stage cluster sampling | Two-Phase Sampling |
| Kapcsolódó≠ | 5 | 4 |
| Összefoglaló≠ | 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. |
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