Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Адаптивная простая случайная выборка× | Простая случайная выборка× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1990–1992 | Early 20th century; systematized by Cochran 1953/1977 |
| Автор метода≠ | Steven K. Thompson | William Gosset, Jerzy Neyman, and formalized by William Cochran |
| Тип≠ | Probability-based adaptive sampling design | Probability sampling design |
| Основополагающий источник≠ | Thompson, S. K. (1992). Sampling. John Wiley & Sons. ISBN: 978-0471548850 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| Другие названия | ASRS, adaptive SRS, adaptive random sampling, sequential adaptive sampling | SRS, unrestricted random sampling, equal-probability sampling, EPSEM |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Adaptive simple random sampling (ASRS) begins with a conventional simple random sample and then expands the sample in regions where the variable of interest exceeds a pre-specified threshold. Units neighboring a qualifying observation are added to the sample, allowing the design to concentrate effort where the population is dense or rare, while retaining unbiased estimation through the Horvitz-Thompson or Hansen-Hurwitz estimators. The approach was systematized by Steven K. Thompson in the early 1990s as part of the broader adaptive sampling framework. | 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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