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Proporcionální stratifikovaný výběr×Disproportional Stratified Sampling×
OborMetodologie dotazníkových šetřeníMetodologie dotazníkových šetření
RodinaProcess / pipelineProcess / pipeline
Rok vzniku1953–1965 (formalized in survey sampling literature)1934
TvůrceWilliam G. Cochran; Leslie KishJerzy Neyman
TypProbability sampling designProbability sampling design
Původní zdrojCochran, 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
Další názvyproportionate stratified sampling, proportional allocation stratified sampling, PSRS, proportionate stratified random samplingdisproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling
Příbuzné66
ShrnutíProportional stratified sampling divides the target population into non-overlapping strata (subgroups defined by a key characteristic such as age band, region, or gender) and then draws a simple random sample from each stratum so that each stratum's share of the total sample matches its share of the total population. Because each subgroup is represented in exact proportion to its population weight, the resulting sample mirrors the population structure closely without requiring post-hoc weighting adjustments.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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ScholarGatePorovnat metody: Proportional Stratified Sampling · Disproportional Stratified Sampling. Získáno 2026-06-19 z https://scholargate.app/cs/compare