Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Стратифицированная выборка с непропорциональным распределением× | Простая случайная выборка× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1934 | Early 20th century; systematized by Cochran 1953/1977 |
| Автор метода≠ | Jerzy Neyman | William Gosset, Jerzy Neyman, and formalized by William Cochran |
| Тип | Probability sampling design | Probability sampling design |
| Основополагающий источник | 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 |
| Другие названия | disproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling | SRS, unrestricted random sampling, equal-probability sampling, EPSEM |
| Связанные | 6 | 6 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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