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Lĩnh vựcPhương pháp luận khảo sátPhương pháp luận khảo sát
HọProcess / pipelineProcess / pipeline
Năm ra đời1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990sMid-20th century (Cochran 1953; Kish 1965)
Người khởi xướngW. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologistsWilliam G. Cochran; formalized in survey sampling theory
LoạiProbability sampling designProbability sampling design
Công trình gốcCochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Tên gọi kháchierarchical cluster sampling, nested cluster sampling, multi-stage cluster sampling, clustered multilevel samplinginterval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Liên quan65
Tóm tắtMulti-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.
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ScholarGateSo sánh phương pháp: Multi-level Cluster Sampling · Systematic Sampling. Truy cập ngày 2026-06-15 từ https://scholargate.app/vi/compare