SECTION 3.2 Summary

• A sample survey selects a sample from the population that is the object of our study. We base conclusions about the population on data collected from the sample.
• The design of a sample refers to the method used to select the sample from the population. Probability sampling designs use impersonal chance to select a sample.
• The basic probability sample is a simple random sample (SRS). An SRS gives every possible sample of a given size the same chance to be chosen.
• Choose an SRS by labeling the members of the population and using a table of random digits to select the sample. Software can automate this process.
• To choose a stratified random sample, divide the population into strata, or groups of cases that are similar in some way that is important to the response. Then choose a separate SRS from each stratum, and combine them to form the full sample.
• Multistage samples select successively smaller groups within the population in stages, resulting in a sample consisting of clusters of cases. Each stage may employ an SRS, a stratified sample, or another type of sample.
• Failure to use probability sampling often results in bias, or systematic errors in the way the sample represents the population. Voluntary response samples, in which the respondents choose themselves, are particularly prone to large bias.
• In human populations, even probability samples can suffer from bias due to undercoverage or nonresponse, from response bias due to the behavior of the interviewer or the respondent, or from misleading results due to poorly worded questions.