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분야조사방법론조사방법론
계열Process / pipelineProcess / pipeline
기원 연도1934 (Neyman's stratified sampling theory); field applications throughout 20th centuryMid-20th century (Cochran 1953; Kish 1965)
창시자Jerzy Neyman (stratified sampling theory); applied broadly in field survey practiceWilliam G. Cochran; formalized in survey sampling theory
유형Probability sampling designProbability sampling design
원전Cochran, 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
별칭field stratified sampling, stratified field survey sampling, in-field stratified sampling, field survey stratificationinterval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
관련65
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.Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity.
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ScholarGate방법 비교: Field-based Stratified Sampling · Systematic Sampling. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare