Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Divu pakāpju izlase× | Stratificētā izlase× | |
|---|---|---|
| Nozare≠ | Izlases veidošana | Aptauju metodoloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1938 | 1977 |
| Autors≠ | Jerzy Neyman | William G. Cochran |
| Tips≠ | Multi-phase sampling design | Probability-based survey sampling design |
| Pirmavots≠ | Neyman, J. (1938). Contribution to the theory of sampling human populations. Journal of the American Statistical Association, 33(201), 101–116. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7 |
| Citi nosaukumi≠ | Two-Phase Sampling | Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme |
| Saistītās≠ | 4 | 2 |
| Kopsavilkums≠ | Double Sampling (also called two-phase or multistage sampling) is a survey design in which a large preliminary sample is collected using inexpensive methods or partial information, then a smaller subsample is drawn from it and measured in detail. Pioneered by Jerzy Neyman in 1938, it is particularly useful when a cheap surrogate measurement is available but true measurement is expensive. | 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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