Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Vienkāršā nejaušā izlase× | Daudpakāpju izlase× | |
|---|---|---|
| Nozare | Aptauju metodoloģija | Aptauju metodoloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | Early 20th century; systematized by Cochran 1953/1977 | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Autors≠ | William Gosset, Jerzy Neyman, and formalized by William Cochran | Leslie Kish; William G. Cochran |
| Tips | Probability sampling design | Probability sampling design |
| Pirmavots≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Citi nosaukumi | SRS, unrestricted random sampling, equal-probability sampling, EPSEM | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | 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. | 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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