A convenience sample , also called a non-probability or opportunity sample , among other names, is a sample drawn without any underlying probability-based selection method. Basically a convenience sample is any data that is neither a complete enumeration of all the possible data—a census—nor a careful, scientific sample. “Convenience samples” are rarely convenient to draw, but they are referred to this way to distinguish them from random samples (see Q2 ). Examples of convenience samples include testimonies presented to NGOs, UN Missions, or truth commissions, lists of airstrikes documented by observing them, text messages coming in from disaster-stricken areas, records collected by police forces during their daily duties, investigation records, and press reports, among many, many others. All of these are important, useful sources of data and many convenience samples are collected through very carefully designed data collection procedures (see, for example, Who Did What to Whom by Patrick Ball). However, the fundamental quality that defines them as convenience samples is the lack of an underlying probability-based selection method. In other words, convenience samples rely on data that is selected by those who provide it or those who observe it – information from individuals who chose to tell their stories to NGOs or reporters, incidents that happen to be witnessed by police, reports from individuals who own a cell phone and have the ability to send a text.
Absent a probability-based selection procedure, it is nearly impossible to describe quantitatively the relationship between a convenience sample and the underlying population of interest (see Q3 ). In other words, it is difficult to quantitatively describe the portions of the population that are included in a convenience sample. An important exception is the case where multiple samples have been collected, making it possible to model the selection process, even if this process was not explicitly planned and described prior to collecting the samples (see Multiple Systems Estimation ).