Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.

Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing study related to a new software launch conducted by a computer software store by interviewing the customers is an example of convenience sampling. The results of convenience sampling may be perfect in some cases and highly biased (favor specific outcomes) in others.

Convenience sampling lacks accuracy since it does not consider the actual representation of the population. However, sometimes, it is the only possible sampling method available. For example, consider a college student doing a term project who wants to know the average soda consumption in the college town on Friday night. He goes to a nearby party to survey soda consumption. If the college town has a small population, mainly consisting of students, and a graduation party is chosen for the survey, the sample has a fair chance to represent the population.

This text is adapted from Openstax, Introductory Statistics, Section 1.2 Data, Sampling, and Variation in Data and Sampling