Сравнение методов

	Многоуровневая кластерная выборка	Систематическая выборка
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s	Mid-20th century (Cochran 1953; Kish 1965)
Автор метода	W. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologists	William G. Cochran; formalized in survey sampling theory
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	interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Связанные	6	5
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.	Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity.