So sánh phương pháp

	Lấy mẫu trường hợp điển hình có trọng số	Chọn mẫu hạn ngạch
Lĩnh vực	Phương pháp luận khảo sát	Phương pháp luận khảo sát
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1990s–2000s (as a mixed-methods extension)	1930s
Người khởi xướng	Derived from Patton's typical case sampling (1990) combined with classical survey weighting principles	Developed in market research and opinion polling, notably applied by George Gallup in the 1930s
Loại	Purposive sampling with probability weighting	Non-probability sampling design
Công trình gốc	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. pp. 236–238 (typical case sampling). ISBN: 978-0761919711	Moser, C. A., & Kalton, G. (1972). Survey Methods in Social Investigation (2nd ed.). Heinemann. ISBN: 978-0435827496
Tên gọi khác	weighted purposive typical sampling, probability-weighted typical case selection, typical case sampling with weighting, weighted representative case sampling	quota-controlled sampling, quota selection, non-probability quota sampling
Liên quan	6	5
Tóm tắt	Weighted typical case sampling combines the purposive logic of typical case selection — choosing cases that represent the modal, average, or most common profile of a population — with post-selection probability weighting. The result is a sample that is both substantively representative (cases reflect the norm) and statistically corrected for differential selection probabilities or population structure. It is used in mixed-methods and survey research where depth of typical examples matters alongside inferential accuracy.	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.