Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Sampuli Awamu nyingi za Uwiano× | Sampuli Iliyowekwa Ngazi× | |
|---|---|---|
| Nyanja | Metodolojia ya Dodoso | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1950s–1960s | 1977 |
| Mwanzilishi≠ | Leslie Kish; William G. Cochran (theoretical foundations) | William G. Cochran |
| Aina≠ | Probability sampling design | Probability-based survey sampling design |
| Chanzo asilia≠ | Kish, L. (1965). Survey Sampling. John Wiley & Sons. (Chapters 6–7 on multistage and PPS designs.) ISBN: 978-0471489009 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7 |
| Majina mbadala | proportional PPS multistage sampling, multistage probability proportional to size sampling, proportionate multistage cluster sampling, PPS multistage sampling | Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme |
| Zinazohusiana≠ | 6 | 2 |
| Muhtasari≠ | Proportional multistage sampling is a probability sampling design that selects units across two or more hierarchical stages — for example, regions, then districts, then households — where the number of units drawn at each stage is proportional to the size of each higher-level unit. By weighting selection probabilities to match cluster size, it produces self-weighting samples that closely mirror the population structure and simplify variance estimation. | Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics. |
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