방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 이중 표본 추출× | 군집 표본 추출× | |
|---|---|---|
| 분야≠ | 표본추출 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1938 | Early-to-mid 20th century; canonical treatment 1953/1977 |
| 창시자≠ | Jerzy Neyman | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| 유형≠ | Multi-phase sampling design | Probability sampling design |
| 원전≠ | Neyman, J. (1938). Contribution to the theory of sampling human populations. Journal of the American Statistical Association, 33(201), 101–116. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| 별칭≠ | Two-Phase Sampling | cluster random sampling, area sampling, one-stage cluster sampling |
| 관련≠ | 4 | 5 |
| 요약≠ | Double Sampling (also called two-phase or multistage sampling) is a survey design in which a large preliminary sample is collected using inexpensive methods or partial information, then a smaller subsample is drawn from it and measured in detail. Pioneered by Jerzy Neyman in 1938, it is particularly useful when a cheap surrogate measurement is available but true measurement is expensive. | Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters. |
| ScholarGate데이터셋 ↗ |
|
|