Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Heterogeneity ya Tabaka la Anga× | Sampuli ya Kwenye Kundi (Cluster Sampling)× | |
|---|---|---|
| Nyanja≠ | Usampulishaji | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2010 | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Mwanzilishi≠ | Jinfeng Wang | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Aina≠ | Geographical detection and stratification method | Probability sampling design |
| Chanzo asilia≠ | Wang, J. F., Li, X. H., Christakos, G., Liao, Y. L., Zhang, T., & Gu, X. (2010). Geographical detectors–based health risk assessment and its application in the neural tube defects study for the C–H plane. International Journal of Geographical Information Science, 24(1), 107–127. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Majina mbadala≠ | Geodetector, GeoDetector | cluster random sampling, area sampling, one-stage cluster sampling |
| Zinazohusiana≠ | 3 | 5 |
| Muhtasari≠ | Spatial Stratified Heterogeneity, commonly known as Geodetector, is a framework introduced by Jinfeng Wang and colleagues in 2010 for measuring and detecting spatial heterogeneity in data and identifying environmental risk factors. It quantifies the degree to which a given factor (variable) explains spatial variation in an outcome and is particularly valuable for environmental epidemiology, ecology, and geographical analysis where spatial non-stationarity is common. | 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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