Non-Probability Sampling Methods Explained
In the last article we have seen the description of Probability Sampling Methods.
Now, in this let us look at the various methods of Non-Probability Sampling.
A Non-Probability Sampling Method involves non — random selection based on convenience/ other criteria, allowing to easily collect initial data. Individuals are selected based on non — random criteria and not every individual has a chance of being included. This type of sampling is easier to access, but you cant use it to make a valid statistical inferences about the whole population.
Under Non-Probability Sampling:-
1. Convenience Sampling
2. Voluntary Response Sampling
3. Purposive Sampling
4. Snowball Sampling
Let us see each method in detail.
1. Convenience Sampling-
Simply includes the individuals who happen to be most accessible to researcher. It is an easy and inexpensive way to gather initial data, but there is no way to tell if sample is representative of population, so it can’t produce generalized results.
E.g. — You are researching opinions about student support services in your university, so after each of your classes, you ask your fellow students to complete a survey on the topic. This is a convenient way to gather data, but as you only surveyed students taking the same classes as you at the same level, the sample is not representative of all the students at your university.
2. Voluntary Response Sampling-
Similar to Convenience sampling, a voluntary response sample is mainly based on ease of access. Instead of researcher choosing participants and directly contacting the, people volunteer themselves.
E.g.- You send out the survey to all students at your university and a lot of students decide to complete it. This can certainly give you some insight into the topic, but the people who responded are more likely to be those who have strong opinions about the student support services, so you can’t be sure that their opinions are representative of all students.
3. Purposive Sampling-
This type of sampling involves researcher using their judgement to select a sample that is most useful to purposes of research. It is often used in qualitative research, where researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inference.
E.g.- 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-
If population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to as you get in contact with more population.
E.g. — 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.
