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| Онлайн удобна извадка× | Квотен подбор× | |
|---|---|---|
| Област | Методология на проучванията | Методология на проучванията |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1990s–2000s (internet survey era) | 1930s |
| Създател≠ | Evolved from convenience sampling; internet applications documented from mid-1990s onward | Developed in market research and opinion polling, notably applied by George Gallup in the 1930s |
| Тип≠ | Non-probability sampling | Non-probability sampling design |
| Основополагащ източник≠ | Gosling, S. D., Vazire, S., Srivastava, S., & John, O. P. (2004). Should we trust web-based studies? A comparative analysis of six preconceptions about internet questionnaires. American Psychologist, 59(2), 93–104. DOI ↗ | Moser, C. A., & Kalton, G. (1972). Survey Methods in Social Investigation (2nd ed.). Heinemann. ISBN: 978-0435827496 |
| Други названия≠ | web-based convenience sampling, internet convenience sampling, digital convenience sampling, online accidental sampling | quota-controlled sampling, quota selection, non-probability quota sampling |
| Свързани≠ | 3 | 5 |
| Резюме≠ | Online convenience sampling is a non-probability technique in which participants are recruited via internet channels — survey platforms, social media, email lists, or research panels — simply because they are accessible and willing to respond. It is the online analogue of traditional convenience sampling, offering fast, low-cost data collection at the expense of known representativeness. It is among the most widely used approaches in social, behavioral, and health sciences research conducted through web-based surveys. | 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. |
| ScholarGateНабор от данни ↗ |
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