Snowball sampling is often used when interviewing. Instead randomly asking people about a particular topic, you would interview initially a person thought to be knowledgable about a subject and then ask them to identify additional people who could serve as usefull interviewees. You then interview those people and ask them to suggest even more people. Thus, your pool of interviewees increases over time, something akin to making a big snowball where it slowly groes as you add more snow.
What is the difference between quota sampling and cluster sampling
It can be but it is not simple random sampling.
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
What I believe you are referring to is cluster sampling or cluster. In cluster sampling, the population is divided into clusters and all population members in the cluster are sampled.
Multistage sampling is a form of cluster sampling where instead of using the entire cluster, random samples from each cluster are used. This is typically used when doing opinion polls or surveys.
simple random, stratified sampling, cluster sampling
Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling
There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.
Answer is Quota sampling. Its one of the method of non-probability sampling.
Advantages of cluster sampling include that it's inexpensive, fast, and simple. A disadvantage is that it is known to have a high sampling error.
cluster sampling
Snowball sampling allows for the recruitment of hard-to-reach populations, such as marginalized or hidden communities. It is particularly useful for studying groups where there is no defined sampling frame. Additionally, it can help build trust and rapport with participants as referrals come from within the community.