Survey Sampling - Non-Probability Sampling

Non-Probability Sampling

Many surveys are not based on a probability samples, but rather by finding a suitable collection of respondents to complete the survey. Some common examples of non-probability sampling are:

• Judgement Samples: A researcher decides which population members to include in the sample based on his or her judgement. The researcher may provide some alternative justification for the representativeness of the sample.
• Snowball Samples: Often used when a target population is rare, members of the target population recruit other members of the population for the survey.
• Quota Samples: The sample is designed to include a designated number of people with certain specified characteristics. For example, 100 coffee drinkers. This type of sampling is common in non-probability market research surveys.
• Convenience Samples: The sample is composed of whatever persons can be most easily accessed to fill out the survey.

In non-probability samples the relationship between the target population and the survey sample is immeasurable and potential bias is unknowable. Sophisticated users of non-probability survey samples tend to view the survey as an experimental condition, rather than a tool for population measurement, and examine the results for internally consistent relationships.