Editing Survey sampling (section)

==Non-probability sampling==

Many surveys are not based on probability samples, but rather on finding a suitable collection of respondents to complete the survey.  Some common examples of non-probability sampling are:<ref>{{cite web|url=https://www.statpac.com/surveys/sampling.htm|title=Survey Sampling Methods|website=www.statpac.com}}</ref>
* 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. The underlying assumption is that the investigator will select units that are characteristic of the population. This method can be subjected to researcher's biases and perception.<ref>{{cite web|url=https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch13/nonprob/5214898-eng.htm|title=Learning resources: Statistics: Power from data! Non-probability sampling|first1=Statistics Canada|last1=Government of Canada|first2=Statistics Canada|last2=Government of Canada|date=28 January 2009|website=www150.statcan.gc.ca}}</ref>
* 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 sampling|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 sample|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.