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DziedzinaMetodologia badań sondażowychMetodologia badań sondażowych
RodzinaProcess / pipelineProcess / pipeline
Rok powstania1953–19651934
TwórcaLeslie Kish; William G. CochranJerzy Neyman
TypProbability sampling with weightingProbability sampling design
Źródło pierwotneCochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Inne nazwystratified sampling with weights, design-weighted stratified sampling, post-stratification weighting, WSSdisproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling
Pokrewne66
PodsumowanieWeighted stratified sampling divides a population into non-overlapping strata and draws a probability sample from each stratum, then attaches a design weight to every selected unit so that estimates correctly represent the full population. Weights compensate for unequal selection probabilities that arise from disproportionate stratum allocations, non-response, or frame imperfections, making the procedure the backbone of most large-scale national and international surveys.Disproportional stratified sampling divides the population into mutually exclusive strata and deliberately draws different proportions from each stratum — oversampling small or analytically important subgroups and undersampling large ones. Post-hoc weighting restores population-level representativeness when overall estimates are needed. First formalised by Jerzy Neyman in 1934, it is the standard approach when subgroup-level precision matters as much as total-population estimates.
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ScholarGatePorównaj metody: Weighted Stratified Sampling · Disproportional Stratified Sampling. Pobrano 2026-06-19 z https://scholargate.app/pl/compare