Сравнение методов

	Кластерная выборка с непропорциональным распределением	Систематическая выборка
Область	Методология опросов	Методология опросов
Семейство	Process / pipeline	Process / pipeline
Год появления	Mid-20th century (formalised 1950s–1965)	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: 978-0471489009	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Другие названия	disproportionate cluster sampling, unequal-probability cluster sampling, variable-rate cluster sampling, non-proportional cluster sampling	interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Связанные	6	5
Сводка	Disproportional cluster sampling is a probability-based survey design in which naturally occurring groups (clusters) are selected as primary sampling units, but the number of clusters or elements drawn from each group is not proportional to that group's share of the population. By deliberately over- or under-sampling certain clusters, researchers gain analytic flexibility and precision where it matters most, at the cost of requiring post-hoc weighting for population-level inference.	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.