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| 가중 표본 추출× | 단순 무작위 표본 추출(SRS)× | |
|---|---|---|
| 분야 | 조사방법론 | 조사방법론 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator) | Early 20th century; systematized by Cochran 1953/1977 |
| 창시자≠ | Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework) | William Gosset, Jerzy Neyman, and formalized by William Cochran |
| 유형 | Probability sampling design | Probability 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.). John Wiley & Sons. ISBN: 978-0471162407 |
| 별칭 | probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling | SRS, unrestricted random sampling, equal-probability sampling, EPSEM |
| 관련 | 6 | 6 |
| 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. | Simple random sampling (SRS) is the foundational probability sampling method in which every unit in the population has an equal and independent chance of being selected. Because selection is governed purely by chance, SRS eliminates systematic bias, supports unbiased estimation of population parameters, and provides the statistical baseline against which all more complex probability designs are evaluated. |
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