Basic notions of sampling. Simple random sampling: estimation of the population mean, population total and a proportion. Confidence intervals for these parameters and choosing the appropriate sample size. Random sampling with replacement and estimation of parameters. Stratified random sampling: stratification principle, estimation of the population mean, population total and a proportion. Methods of choosing the sample size, proportional allocation of sample sizes and Neyman allocation. Systematic sampling. Ratio and regression estimators. Cluster sampling (one stage, two stage, etc.) and estimation of parameters. Unequal probability sampling, Horvitz-Thompson estimator.