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Salīdzināt metodes

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Stratificētā izlase ar proporcionālu sadalījumu×Neproporcionāla stratificēta paraugu ņemšana×
NozareAptauju metodoloģijaAptauju metodoloģija
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads1953–1965 (formalized in survey sampling literature)1934
AutorsWilliam G. Cochran; Leslie KishJerzy Neyman
TipsProbability sampling designProbability sampling design
PirmavotsCochran, 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
Citi nosaukumiproportionate stratified sampling, proportional allocation stratified sampling, PSRS, proportionate stratified random samplingdisproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling
Saistītās66
KopsavilkumsProportional 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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ScholarGateSalīdzināt metodes: Proportional Stratified Sampling · Disproportional Stratified Sampling. Izgūts 2026-06-19 no https://scholargate.app/lv/compare