Non-Random sampling or non-probability sampling is a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. This sampling method depends heavily on the expertise of the researchers. The researchers use it widely for qualitative research. It is cheaper to do than random sampling.
There are essentially 5 types of non-random sampling methods:
1. Convenience Sampling – A convenience sample simply includes the individuals who happen to be most accessible to the researcher. You ask your classmates to answer a survey or go directly to people in a line at a supermarket
2. Voluntary response sampling – Similar to convenience sampling, but here to get to more people, and do less face-to-face work, you send out a survey to all students at college
3. Purposive/judgment/authoritative sampling – Often used in qualitative research. The researcher uses his expertise to select a sample that is most useful to the purpose of the research.
You want to know more about the opinions and experiences of disabled students at your university, so you purposefully select a number of students with different support needs in order to gather a varied range of data on their experiences with student services.
4. Snowball sampling – You want to know more about the opinions and experiences of disabled students at your university, so you purposefully select a number of students with different support needs in order to gather a varied range of data on their experiences with student services.
You are researching experiences of homelessness in your city. Since there is no list of all homeless people in the city, probability sampling isn’t possible. You meet one person who agrees to participate in the research, and she puts you in contact with other homeless people that she knows in the area.
5. Quota sampling – Quota sampling is defined as a non-probability sampling method in which researchers create a sample involving individuals that represent a population. Researchers choose these individuals according to specific traits or qualities.
A cigarette company wants to find out what age group prefers what brand of cigarettes in a particular city. He/she applies quotas on the age groups of 21-30, 31-40, 41-50, and 51+. From this information, the researcher gauges the smoking trend among the population of the city.
Quota sampling is somewhat similar to stratified sampling, which is probability sampling, in that similar units are grouped together. However, it differs in how the units are selected.
