Appendix B Finite Population Inference

A fundamental question in survey analysis is to identify which probability measure governs the inference. In classical statistical inference, the available observations are usually assumed to be independent and identically distributed (IID) random variables. Under this approach, randomness comes from the model that generates the data. However, as Kish (1987) notes, this assumption does not adequately describe information from surveys with complex sample designs, where observations are selected through stratification, clustering, and unequal inclusion probabilities.

References

Kish, L. (1987). Statistical design for research. John Wiley & Sons.