When writing an undergraduate or master's level dissertation, you can utilize one of **five non-probability sampling techniques**: quota sampling, convenience sampling, purposive sampling, self-selection sampling, and snowball sampling. Each method has its own advantages and disadvantages. For example, quota sampling is ideal when selecting a sample of cases for study because you can be sure that each item in the sample represents exactly 1 percent of the population. Convenience sampling is easy to implement but may not provide **reliable information** due to the fact that certain groups of people are likely to be more or less available depending on their preferences or activities.

In addition to these five common methods, there are several others that can be useful in specific situations. For example, if you were doing a survey on drug use among **high school students**, then probability sampling would not be appropriate because it is difficult to estimate how many individuals exist within a population based on statistics alone. Instead, a non-probability approach would be needed to select some type of sample from all of the students in the nation's high schools. This could be done by using school district lists as a starting point and then randomly selecting students from within those districts until the desired number had been selected.

Non-probability approaches can also be useful when you do not have enough time to complete a probability sample.

- What are the types of nonprobability sampling?
- What are the types of non-probability sampling?
- What is non-probability sampling with examples?
- What are the four types of non-probability sampling?
- What are the types of non-random sampling?
- Why are non-probability sampling methods used in statistics?
- Is purposive sampling a non-probability test?

Convenience sampling, voluntary response sampling, purposive sampling, snowball sampling, and quota sampling are examples of **non-probability sampling procedures**. Non-probability samples are useful in surveys that include sensitive topics or where you do not want to use probability sampling because of time constraints or complexity of the population being surveyed.

In convenience sampling, participants are chosen from among those available at the time and place of the survey. This type of sample is easy to obtain but may not be representative of **the entire population**.

Voluntary response sampling involves contacting randomly selected individuals by mail or telephone and asking them to complete a survey on behalf of all eligible people in their household. People are selected for the survey using random number generators or other methods. The sample can then be weighted based on gender, age, region, or any other characteristic relevant to your study. Voluntary response sampling is useful when it is not feasible or appropriate to approach every person within the defined population.

Purposeful sampling is similar to **convenience sampling** but includes criteria for selecting participants. For example, participants could be chosen to represent different regions of the country, levels of education, or types of businesses. Purposeful sampling allows researchers to make certain that participants are representing **the entire spectrum** of the population being studied.

Convenience sampling, voluntary response sampling, purposive sampling, snowball sampling, and quota sampling are among **common non-probability sampling approaches**...

Nonprobability Sampler

- Accidental, Haphazard or Convenience Sampling. One of the most common methods of sampling goes under the various titles listed here.
- Purposive Sampling. In purposive sampling, we sample with a purpose in mind.
- Modal Instance Sampling.
- Expert Sampling.
- Quota Sampling.
- Heterogeneity Sampling.
- Snowball Sampling.

Nonprobability Sampler

- Accidental, Haphazard or Convenience Sampling. One of the most common methods of sampling goes under the various titles listed here.
- Purposive Sampling.
- Modal Instance Sampling.
- Expert Sampling.
- Quota Sampling.
- Heterogeneity Sampling.
- Snowball Sampling.

Non-probability sampling methods are another type of sampling method since not every member of a population has an equal chance of being chosen to be in the sample. This sampling approach is sometimes employed because it is less expensive and more convenient than **probability sampling methods**. For example, if a researcher wants to learn about the demographics of his or her students, it would be less burdensome to ask all of them rather than randomly selecting a subset of them.

Non-probability samples can be classified as either convenience or volumetric. Convenience samples are selected from among those individuals who agree to participate by whatever method is easiest for the researcher. These samples often have significant biases against members of underrepresented groups. For example, if a researcher wanted to find out what universities students at large prefer, he or she could simply ask all of the students at these schools. This would give a good idea of how popular they are, but it would also be very biased - students at larger schools are likely to be more interested in answering surveys, so this sample would not be representative of all students at these schools.

Voluminous samples are drawn from larger populations by multiplying the number of required samples by a factor. For example, if a researcher needed to learn about the demographics of students at a large university, he or she might want to survey only 100 people. To avoid bias, each person chosen would need to be representative of the entire student body.

Non-Probability Sampling Methods It's also known as chance sampling, opportunity sampling, or grab sampling. Purposive sampling: a method in which the researcher selects a sample based on their knowledge of the population and the study itself. The research participants are chosen depending on the study's purpose. For example, if I wanted to select students at my school who drink alcohol, I would go to the student council office and ask for the list of names of all the students who do drink alcohol. I could then write them a letter asking them about alcohol use at my school and what effects it has on their lives. This is purposive sampling because I selected these students based on their knowledge that they drink alcohol and then wrote them a letter asking them about alcohol.

Purposive sampling can be difficult to do well because you need to make sure that you include **enough variation** in **your sample** so that you aren't just looking at one part of the population. For example, if you sampled only from one gender or ethnic group, you might not get good results because there could be differences between **those groups** that you wouldn't see if everything was treated equally.

In addition, purposive sampling can be time consuming. If you want to find out more about a specific topic at your school or with your community, this is a great way to do it. But it can also be hard work if you don't know where to look first.