Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Стратифицированная выборка× | Взвешивание и калибровка выборок× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1977 | 2010 |
| Автор метода≠ | William G. Cochran | Sharon Lohr |
| Тип≠ | Probability-based survey sampling design | Estimation adjustment procedure |
| Основополагающий источник≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7 | Lohr, S. L. (2010). Sampling: Design and Analysis (2nd ed.). Brooks/Cole. ISBN: 978-0-495-10527-5 |
| Другие названия | Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme | Survey Calibration, Post-Stratification Weighting, Raking Adjustment, Ağırlıklandırma (Anket) |
| Связанные≠ | 2 | 3 |
| Сводка≠ | 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. | Survey weighting is a statistical procedure that assigns a numeric weight to each sampled unit so that the weighted sample reproduces known population totals. Rooted in classical sampling theory and systematically synthesized by Sharon Lohr (2010), the approach corrects for unequal selection probabilities, unit nonresponse, and coverage gaps, producing estimates that are more representative of the target population than raw sample means or totals would be. |
| ScholarGateНабор данных ↗ |
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