Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Muestreo por cuotas ponderado× | Muestreo por cuotas× | |
|---|---|---|
| Campo | Metodología de encuestas | Metodología de encuestas |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | Mid-to-late 20th century | 1930s |
| Autor original≠ | Derived from quota sampling (mid-20th century market research) combined with survey weighting theory (Kalton, 1983) | Developed in market research and opinion polling, notably applied by George Gallup in the 1930s |
| Tipo≠ | Non-probability sampling with post-collection weight adjustment | Non-probability sampling design |
| Fuente seminal≠ | Kalton, G. (1983). Introduction to Survey Sampling. Sage Publications. ISBN: 978-0803921290 | Moser, C. A., & Kalton, G. (1972). Survey Methods in Social Investigation (2nd ed.). Heinemann. ISBN: 978-0435827496 |
| Alias≠ | quota sampling with weighting, weighted quota survey, post-weighted quota sampling, quota sample weighting | quota-controlled sampling, quota selection, non-probability quota sampling |
| Relacionados | 5 | 5 |
| Resumen≠ | Weighted quota sampling combines quota sampling — recruiting a set number of respondents matching pre-specified demographic cells — with post-collection statistical weighting that adjusts each respondent's contribution to match known population proportions. The result is a non-probability design with a bias-correction mechanism, widely used in market research, political polling, and applied social surveys when probability sampling is impractical but representativeness remains a goal. | Quota sampling is a non-probability technique in which the researcher pre-specifies how many units to recruit from each subgroup (quota cell) defined by one or more control variables such as age, gender, or occupation. Interviewers or data collectors then use their own judgment to find and enroll participants until each cell is filled. The method guarantees the sample mirrors the population on the control variables but does not provide the randomness needed for classical statistical inference. |
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