পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| অনলাইন ওয়েটেড স্যাম্পলিং× | ওয়েটেড স্যাম্পলিং× | |
|---|---|---|
| ক্ষেত্র | জরিপ পদ্ধতি | জরিপ পদ্ধতি |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | Late 1990s–2000s | 1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator) |
| প্রবর্তক≠ | Survey methodology practitioners; systematized via probability-based online panels (e.g., Knowledge Networks, founded late 1990s) | Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework) |
| ধরন≠ | Probability-adjusted online sampling technique | Probability sampling design |
| মৌলিক উৎস≠ | Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method (4th ed.). Wiley. ISBN: 978-1118456149 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| অপর নাম | web-based weighted sampling, internet survey weighting, online panel weighting, weighted internet sampling | probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling |
| সম্পর্কিত≠ | 4 | 6 |
| সারসংক্ষেপ≠ | Online weighted sampling is the practice of recruiting respondents via internet platforms and then applying statistical weights to correct for unequal selection probabilities, coverage gaps, and differential non-response. It enables researchers to draw valid population inferences from web surveys by compensating for the structural biases inherent in online recruitment — including the fact that not all members of a target population have equal internet access or equal likelihood of joining a panel. | Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient. |
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