Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Sampuli ya Kwenye Kundi (Cluster Sampling)× | Usampulishaji wa Hatua Nyingi× | |
|---|---|---|
| Nyanja | Metodolojia ya Dodoso | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | Early-to-mid 20th century; canonical treatment 1953/1977 | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Mwanzilishi≠ | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice | Leslie Kish; William G. Cochran |
| Aina | Probability sampling design | Probability sampling design |
| Chanzo asilia≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Majina mbadala≠ | cluster random sampling, area sampling, one-stage cluster sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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. | Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage. |
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