Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Usampulishaji wa Hatua Nyingi× | Usampulishaji Rahisi wa Nasibu× | |
|---|---|---|
| Nyanja | Metodolojia ya Dodoso | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) | Early 20th century; systematized by Cochran 1953/1977 |
| Mwanzilishi≠ | Leslie Kish; William G. Cochran | William Gosset, Jerzy Neyman, and formalized by William Cochran |
| Aina | Probability sampling design | Probability sampling design |
| Chanzo asilia≠ | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| Majina mbadala | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling | SRS, unrestricted random sampling, equal-probability sampling, EPSEM |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | 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. | Simple random sampling (SRS) is the foundational probability sampling method in which every unit in the population has an equal and independent chance of being selected. Because selection is governed purely by chance, SRS eliminates systematic bias, supports unbiased estimation of population parameters, and provides the statistical baseline against which all more complex probability designs are evaluated. |
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