Syllabus
1. Basic concepts: Population, sampling frame. population vs. sampling total and mean.
2. Simple random sampling without replacement.
3. Systematic sampling.
4. Sampling with unequal probabilities - Poisson sampling and its modifications.
5. Stratified sampling and optimal allocation.
6. Model assisted estimation - ratio and regression estimators, calibration model.
7. Cluster and two-stage sampling.
8. Nonresponse.
Annotation
Basic methods of probability sampling from finite populations.
Estimation of characteristics of finite populations. Applications in sampling surveys.