Krahasoni metodat

	Most standard convenience sampling	Kampionimi me kuota
Fusha	Metodologjia e anketave	Metodologjia e anketave
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1990s–2000s (internet survey era)	1930s
Krijuesi	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
Lloji	Non-probability sampling	Non-probability sampling design
Burimi themelues	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.	Moser, C. A., & Kalton, G. (1972). Survey Methods in Social Investigation (2nd ed.). Heinemann. ISBN: 978-0435827496
Emërtime të tjera	web-based convenience sampling, internet convenience sampling, digital convenience sampling, online accidental sampling	quota-controlled sampling, quota selection, non-probability quota sampling
Të lidhura	3	5
Përmbledhja	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.