Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Muestreo doble× | Muestreo por conglomerados× | |
|---|---|---|
| Campo≠ | Muestreo | Metodología de encuestas |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1938 | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Autor original≠ | Jerzy Neyman | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Tipo≠ | Multi-phase sampling design | Probability sampling design |
| Fuente seminal≠ | Neyman, J. (1938). Contribution to the theory of sampling human populations. Journal of the American Statistical Association, 33(201), 101–116. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Alias≠ | Two-Phase Sampling | cluster random sampling, area sampling, one-stage cluster sampling |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | 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. | 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. |
| ScholarGateConjunto de datos ↗ |
|
|