Reviews sampling methods used in surveys: simple random sampling, systematic sampling, stratification, cluster and multi-stage sampling, sampling with probability proportional to size, two-phase sampling, replicated sampling, panel designs, and non-probability sampling. Kalton discusses issues of practical implementation, including frame problems and non-response, and gives examples of sample designs for a national face-to-face interview survey and for a telephone survey. He also treats the use of weights in survey analysis, the computation of sampling errors with complex sampling designs, and the determination of sample size.

Simple Random Sampling

Simple random sampling (SRS) provides a natural starting point for a discussion of probability sampling methods, not because it is widely used—it is not—but because it is the simplest method and it underlies many of the more complex methods. As a prelude to defining simple random sampling, we will introduce the notation that the sample size is given by n and the population size by N. Then, formally defined, simple random sampling is a sampling scheme with the property that any of the possible subsets of n distinct elements from the population of N elements is equally likely to be the chosen sample. This definition implies that every element in the population has the same probability of being selected for the sample, but ...

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