Written for students and researchers who wish to understand the conceptual and practical aspects of sampling, this book is designed to be accessible without requiring advanced statistical training. It covers a wide range of topics, from the basics of sampling to special topics such as sampling rare populations, sampling organizational populations, and sampling visitors to a place. Using cases and examples to illustrate sampling principles and procedures, the book thoroughly covers the fundamentals of modern survey sampling, and addresses recent changes in the survey environment such as declining response rates, the rise of Internet surveys, the need to accommodate cell phones in telephone surveys, and emerging uses of social media and big data.

Stratified Sampling

Our discussion of sample size in the previous chapter presumes that a simple random sample will be drawn. There also are situations in which the cost-effectiveness of a research project can be improved by using stratified sampling to reduce sampling errors or cluster sampling to reduce costs. This chapter discusses stratified sampling.

Stratified sampling separates the population into subgroups that are called “strata” and then selects random samples from each subgroup (see Exhibit 5.1 for a graphic depiction). Dividing the sampling effort in this fashion creates some extra work and extra cost. However, under some conditions, the estimates drawn from stratified samples have much lower sampling errors than estimates from simple random samples of the same size. This allows sampling error goals to ...

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