Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Eșantionare ponderată× | Eșantionarea pe grupe (Cluster Sampling)× | |
|---|---|---|
| Domeniu | Metodologia anchetelor | Metodologia anchetelor |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator) | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Autorul original≠ | Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework) | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Tip | Probability sampling design | Probability sampling design |
| Sursa seminală≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Denumiri alternative≠ | probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling | cluster random sampling, area sampling, one-stage cluster sampling |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient. | 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. |
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