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Amostragem em Múltiplos Estágios×Amostragem Estratificada×
ÁreaMetodologia de surveyMetodologia de survey
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1950s–1960s (formalized in Kish 1965 and Cochran 1977)1977
Autor originalLeslie Kish; William G. CochranWilliam G. Cochran
TipoProbability sampling designProbability-based survey sampling design
Fonte seminalKish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Outros nomesmultistage cluster sampling, multi-stage sampling, nested sampling, hierarchical samplingProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Relacionados52
ResumoMultistage 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.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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ScholarGateComparar métodos: Multistage Sampling · Stratified Sampling. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare