So sánh phương pháp

	Chọn mẫu phân tầng có trọng số	Lấy mẫu phân tầng không cân đối
Lĩnh vực	Phương pháp luận khảo sát	Phương pháp luận khảo sát
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1953–1965	1934
Người khởi xướng	Leslie Kish; William G. Cochran	Jerzy Neyman
Loại	Probability sampling with weighting	Probability sampling design
Công trình gốc	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
Tên gọi khác	stratified sampling with weights, design-weighted stratified sampling, post-stratification weighting, WSS	disproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling
Liên quan	6	6
Tóm tắt	Weighted stratified sampling divides a population into non-overlapping strata and draws a probability sample from each stratum, then attaches a design weight to every selected unit so that estimates correctly represent the full population. Weights compensate for unequal selection probabilities that arise from disproportionate stratum allocations, non-response, or frame imperfections, making the procedure the backbone of most large-scale national and international surveys.	Disproportional stratified sampling divides the population into mutually exclusive strata and deliberately draws different proportions from each stratum — oversampling small or analytically important subgroups and undersampling large ones. Post-hoc weighting restores population-level representativeness when overall estimates are needed. First formalised by Jerzy Neyman in 1934, it is the standard approach when subgroup-level precision matters as much as total-population estimates.