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স্তরবিন্যস্ত নমুনায়ন (Stratified Sampling)×জরিপ ওয়েটিং এবং ক্যালিব্রেশন×
ক্ষেত্রজরিপ পদ্ধতিজরিপ পদ্ধতি
পরিবারProcess / pipelineProcess / pipeline
উদ্ভবের বছর19772010
প্রবর্তকWilliam G. CochranSharon Lohr
ধরনProbability-based survey sampling designEstimation adjustment procedure
মৌলিক উৎসCochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7Lohr, S. L. (2010). Sampling: Design and Analysis (2nd ed.). Brooks/Cole. ISBN: 978-0-495-10527-5
অপর নামProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı ÖrneklemeSurvey Calibration, Post-Stratification Weighting, Raking Adjustment, Ağırlıklandırma (Anket)
সম্পর্কিত23
সারসংক্ষেপStratified 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.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.
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ScholarGateপদ্ধতির তুলনা করুন: Stratified Sampling · Survey Weighting. 2026-06-18 তারিখে সংগৃহীত, উৎস: https://scholargate.app/bn/compare