विधियों की तुलना करें

	सर्वेक्षण भारण और अंशांकन	स्तरीकृत प्रतिचयन
क्षेत्र	सर्वेक्षण पद्धति	सर्वेक्षण पद्धति
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	2010	1977
प्रवर्तक	Sharon Lohr	William G. Cochran
प्रकार	Estimation adjustment procedure	Probability-based survey sampling design
मौलिक स्रोत	Lohr, S. L. (2010). Sampling: Design and Analysis (2nd ed.). Brooks/Cole. ISBN: 978-0-495-10527-5	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
उपनाम	Survey Calibration, Post-Stratification Weighting, Raking Adjustment, Ağırlıklandırma (Anket)	Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
संबंधित	3	2
सारांश	Survey weighting is a statistical procedure that assigns a numeric weight to each sampled unit so that the weighted sample reproduces known population totals. Rooted in classical sampling theory and systematically synthesized by Sharon Lohr (2010), the approach corrects for unequal selection probabilities, unit nonresponse, and coverage gaps, producing estimates that are more representative of the target population than raw sample means or totals would be.	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.