Сравнение методов

	Многоступенчатая выборка	Систематическая выборка
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	1950s–1960s (formalized in Kish 1965 and Cochran 1977)	Mid-20th century (Cochran 1953; Kish 1965)
Автор метода	Leslie Kish; William G. Cochran	William G. Cochran; formalized in survey sampling theory
Тип	Probability sampling design	Probability sampling design
Основополагающий источник	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Другие названия	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling	interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Связанные	5	5
Сводка	Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage.	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.