This is a non-random sampling technique where the initial respondents to a survey recruit others for a survey.
Linear snowball sampling is when the first responent recruits one more person for the survey, who in turn recruits one more person for the survey. Number of people surveyed will increase in a linear manner.
The related links provide good discussion of this form of surveying. It is a non-representative sample, but it is an effective means of surveying people with common traits who might otherwise be difficult to find.
For example, I want a statistical profile of people that are "hackers" so every hacker I find, I would ask if I could interview his "fellow hackers."
See related links.
Snowball sampling can be used in a number of circumstances. Sometimes the researcher may be able to identify only a small number of individuals in the target group but these people are likely to known others in the target group, and people that they know will also know more such people-and so on. By including those few initial people in her sample, and asking them to recruit others, the researcher may be able to achieve a useable sample size. Then, sometimes, a researcher is actually more interested in the connections between people, or in other words, social networks. In this case, snowball sampling can be used to identify those connections. Please see the link.
Answer is Quota sampling. Its one of the method of non-probability sampling.
Like snowball sampling, network sampling utilizes a "word of mouth" approach of acquiring participants. Those who are originally recruited suggest further participants. This method allows researchers to access populations that are not easily identifiable, are small in number, private, poorly organized or socially marginalized. Examples of such populations would be sexual minorities, drug users, etc. The advantage of network sampling is that these hard-to-reach populations are penetrated and recruitment is fairly convenient and inexpensive for the researcher. Most research methods experts find that network sampling is just as effective as other, more random methods and rarely leads to validity or reliability errors.
1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling 5) Probability proportional to size sampling 6) Matched random sampling 7) Quota sampling 8) Convenience sampling 9) Line-intercept sampling 10) Panel sampling
What is the difference between quota sampling and cluster sampling
Linear snowball sampling is when the first responent recruits one more person for the survey, who in turn recruits one more person for the survey. Number of people surveyed will increase in a linear manner.Read more: What_is_linear_snowball_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.
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.
Snowball sampling involves getting participants to refer others who could also take part. An advantage is that it allows you to recruit deviant groups such as drug users more easily. A disadvantage is that it may not always result in a representative sample.
When building up a demographic profile of the environmentally friendly consumer, you should use snowball sampling to ensure that all ages is represented.
This is a non-random sampling technique where the initial respondents to a survey recruit others for a survey. Linear snowball sampling is when the first responent recruits one more person for the survey, who in turn recruits one more person for the survey. Number of people surveyed will increase in a linear manner. The related links provide good discussion of this form of surveying. It is a non-representative sample, but it is an effective means of surveying people with common traits who might otherwise be difficult to find. For example, I want a statistical profile of people that are "hackers" so every hacker I find, I would ask if I could interview his "fellow hackers." See related links.
The related web sites give a good idea of the types of non-random sampling. These include snowball, convenience, quota, self-selection, diversity, expert, and others. Non-randon sampling is usually done because it is less expensive, easier, and quicker than random sampling.
Snowball sampling can be used in a number of circumstances. Sometimes the researcher may be able to identify only a small number of individuals in the target group but these people are likely to known others in the target group, and people that they know will also know more such people-and so on. By including those few initial people in her sample, and asking them to recruit others, the researcher may be able to achieve a useable sample size. Then, sometimes, a researcher is actually more interested in the connections between people, or in other words, social networks. In this case, snowball sampling can be used to identify those connections. Please see the link.
H. L. Koul has written: 'Weighted empiricals and linear models' -- subject(s): Autoregression (Statistics), Linear models (Statistics), Regression analysis, Sampling (Statistics) 'Weighted empirical processes in dynamic nonlinear models' -- subject(s): Autoregression (Statistics), Linear models (Statistics), Regression analysis, Sampling (Statistics)
B. D. Tikkiwal has written: 'T-classes of linear estimators and the theory of successive sampling' -- subject(s): Estimation theory, Sampling (Statistics)
Use snowball sampling!!! The best sampling method there is! Yeah!! WOohOo!!
Qualitative data sampling involves selecting a subset of individuals, cases, or events that represent various perspectives and experiences relevant to the research question. This process helps researchers gather rich and in-depth information to analyze and interpret patterns, themes, and relationships. Sampling strategies in qualitative research may include purposeful sampling, snowball sampling, or random sampling techniques.