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Proporcionalā daudzpakāpju izlase×Stratificētā izlase×
NozareAptauju metodoloģijaAptauju metodoloģija
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads1950s–1960s1977
AutorsLeslie Kish; William G. Cochran (theoretical foundations)William G. Cochran
TipsProbability sampling designProbability-based survey sampling design
PirmavotsKish, L. (1965). Survey Sampling. John Wiley & Sons. (Chapters 6–7 on multistage and PPS designs.) ISBN: 978-0471489009Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Citi nosaukumiproportional PPS multistage sampling, multistage probability proportional to size sampling, proportionate multistage cluster sampling, PPS multistage samplingProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Saistītās62
KopsavilkumsProportional multistage sampling is a probability sampling design that selects units across two or more hierarchical stages — for example, regions, then districts, then households — where the number of units drawn at each stage is proportional to the size of each higher-level unit. By weighting selection probabilities to match cluster size, it produces self-weighting samples that closely mirror the population structure and simplify variance estimation.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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ScholarGateSalīdzināt metodes: Proportional Multistage Sampling · Stratified Sampling. Izgūts 2026-06-18 no https://scholargate.app/lv/compare