Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Campionamento a grappoli basato sul campo× | Campionamento Sistematico× | |
|---|---|---|
| Campo | Metodologia delle indagini | Metodologia delle indagini |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1950s (theory); 1970s–1980s (field survey practice) | Mid-20th century (Cochran 1953; Kish 1965) |
| Ideatore≠ | William G. Cochran (theoretical foundations); WHO EPI programme (field application) | William G. Cochran; formalized in survey sampling theory |
| Tipo | Probability sampling design | Probability sampling design |
| Fonte seminale≠ | World Health Organization. (1991). Training for mid-level managers: The EPI coverage survey. WHO/EPI/MLM/91.10. World Health Organization. link ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| Alias | field cluster sampling, in-field cluster sampling, area cluster sampling (field), field survey cluster design | interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling |
| Correlati≠ | 6 | 5 |
| Sintesi≠ | Field-based cluster sampling is a probability sampling method in which naturally occurring geographic or administrative groups (clusters) are first randomly selected, and then data are collected in person from units within those clusters. It is the standard design for large-scale field surveys in public health, agriculture, education, and humanitarian response, where compiling a full population list is impractical but clusters such as villages, schools, or census tracts can be identified and physically accessed. | Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity. |
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