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| Campionamento Stratificato Pesato× | Campionamento Stratificato Disproporzionale× | |
|---|---|---|
| Campo | Metodologia delle indagini | Metodologia delle indagini |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1953–1965 | 1934 |
| Ideatore≠ | Leslie Kish; William G. Cochran | Jerzy Neyman |
| Tipo≠ | Probability sampling with weighting | Probability sampling design |
| Fonte seminale | 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 |
| Alias | 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 |
| Correlati | 6 | 6 |
| Sintesi≠ | 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. |
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