방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 가중 표본 추출× | 층화 표본 추출× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator) | 1977 |
| 창시자≠ | Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework) | William G. Cochran |
| 유형≠ | Probability sampling design | Probability-based survey sampling design |
| 원전≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7 |
| 별칭 | probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling | Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme |
| 관련≠ | 6 | 2 |
| 요약≠ | Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient. | 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. |
| ScholarGate데이터셋 ↗ |
|
|