Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Neproporcionāla stratificēta paraugu ņemšana× | Vienkāršā nejaušā izlase× | |
|---|---|---|
| Nozare | Aptauju metodoloģija | Aptauju metodoloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1934 | Early 20th century; systematized by Cochran 1953/1977 |
| Autors≠ | Jerzy Neyman | William Gosset, Jerzy Neyman, and formalized by William Cochran |
| Tips | Probability sampling design | Probability sampling design |
| Pirmavots | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| Citi nosaukumi | disproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling | SRS, unrestricted random sampling, equal-probability sampling, EPSEM |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Disproportional stratified sampling divides the population into mutually exclusive strata and deliberately draws different proportions from each stratum — oversampling small or analytically important subgroups and undersampling large ones. Post-hoc weighting restores population-level representativeness when overall estimates are needed. First formalised by Jerzy Neyman in 1934, it is the standard approach when subgroup-level precision matters as much as total-population estimates. | 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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