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DziedzinaDobór próbyMetodologia badań sondażowych
RodzinaProcess / pipelineProcess / pipeline
Rok powstania19521977
TwórcaGlenn A. McIntyreWilliam G. Cochran
TypSampling design methodologyProbability-based survey sampling design
Źródło pierwotneMcIntyre, G. A. (1952). A method for unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research, 3(4), 385–390. DOI ↗Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Inne nazwyRSSProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Pokrewne42
PodsumowanieRanked Set Sampling (RSS) is a data collection method introduced by G. A. McIntyre in 1952 that improves estimation efficiency when visual ranking of units is easier or cheaper than actual measurement. By deliberately selecting and measuring units that are ranked as most likely to yield desired outcomes, RSS reduces variance compared to simple random sampling while maintaining unbiasedness.Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics.
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ScholarGatePorównaj metody: Ranked Set Sampling · Stratified Sampling. Pobrano 2026-06-15 z https://scholargate.app/pl/compare