Сравнение методов

	Многоуровневая кластерная выборка	Простая случайная выборка
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s	Early 20th century; systematized by Cochran 1953/1977
Автор метода	W. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologists	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.). Wiley. ISBN: 978-0471162407	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Другие названия	hierarchical cluster sampling, nested cluster sampling, multi-stage cluster sampling, clustered multilevel sampling	SRS, unrestricted random sampling, equal-probability sampling, EPSEM
Связанные	6	6
Сводка	Multi-level cluster sampling is a probability sampling design for hierarchically structured populations — such as students nested within classrooms within schools within districts. Clusters are randomly selected at each level of the hierarchy before individual units are sampled within the final-level clusters. The design mirrors the natural nesting of real-world populations and enables efficient large-scale data collection while supporting multilevel statistical analysis.	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.