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Salīdzināt metodes

Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Lauka klasteru izlase×Stratificētā izlase×
NozareAptauju metodoloģijaAptauju metodoloģija
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads1950s (theory); 1970s–1980s (field survey practice)1977
AutorsWilliam G. Cochran (theoretical foundations); WHO EPI programme (field application)William G. Cochran
TipsProbability sampling designProbability-based survey sampling design
PirmavotsWorld Health Organization. (1991). Training for mid-level managers: The EPI coverage survey. WHO/EPI/MLM/91.10. World Health Organization. link ↗Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Citi nosaukumifield cluster sampling, in-field cluster sampling, area cluster sampling (field), field survey cluster designProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Saistītās62
KopsavilkumsField-based cluster sampling is a probability sampling method in which naturally occurring geographic or administrative groups (clusters) are first randomly selected, and then data are collected in person from units within those clusters. It is the standard design for large-scale field surveys in public health, agriculture, education, and humanitarian response, where compiling a full population list is impractical but clusters such as villages, schools, or census tracts can be identified and physically accessed.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: Field-based cluster sampling · Stratified Sampling. Izgūts 2026-06-15 no https://scholargate.app/lv/compare