• A sample survey selects a sample from the population of all individuals about which we desire information. We base conclusions about the population on data about 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 using software. This can also be done using a table of random digits to select the sample.
• To choose a stratified random sample, divide the population into strata, groups of individuals 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 random samples select successively smaller groups within the population in stages, resulting in a sample consisting of clusters of individuals. 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.