Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Sampuli Iliyopimwa kwa Tabaka× | Usampulishaji Rahisi wa Nasibu× | |
|---|---|---|
| Nyanja | Metodolojia ya Dodoso | Metodolojia ya Dodoso |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1953–1965 | Early 20th century; systematized by Cochran 1953/1977 |
| Mwanzilishi≠ | Leslie Kish; William G. Cochran | William Gosset, Jerzy Neyman, and formalized by William Cochran |
| Aina≠ | Probability sampling with weighting | Probability sampling design |
| Chanzo asilia | 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 |
| Majina mbadala | stratified sampling with weights, design-weighted stratified sampling, post-stratification weighting, WSS | SRS, unrestricted random sampling, equal-probability sampling, EPSEM |
| Zinazohusiana | 6 | 6 |
| Muhtasari≠ | 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. | 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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