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분야조사방법론조사방법론
계열Process / pipelineProcess / pipeline
기원 연도1934 (Neyman's stratified sampling theory); field applications throughout 20th century1977
창시자Jerzy Neyman (stratified sampling theory); applied broadly in field survey practiceWilliam G. Cochran
유형Probability sampling designProbability-based survey sampling design
원전Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
별칭field stratified sampling, stratified field survey sampling, in-field stratified sampling, field survey stratificationProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
관련62
요약Field-based stratified sampling divides a geographically dispersed or heterogeneous target population into internally homogeneous subgroups (strata) defined by features observable in the field — such as land use type, habitat zone, administrative district, or community category — and then independently draws random samples from each stratum during on-site data collection. The approach combines the precision gains of stratification with the logistical realities of fieldwork, ensuring that every identifiable subgroup of the landscape or community is represented in the final data set.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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