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In sociology and statistics research, snowball sampling [1] (or chain sampling, chain-referral sampling, referral sampling [2] [3]) is a nonprobability sampling technique where existing study subjects recruit future subjects from among their acquaintances. Thus the sample group is said to grow like a rolling snowball.
Judgment sampling or purposive sampling, where the researcher chooses the sample based on who they think would be appropriate for the study. This is used primarily when there is a limited number of people that have expertise in the area being researched, or when the interest of the research is on a specific field or a small group.
Nonprobability sampling methods include convenience sampling, quota sampling, and purposive sampling. In addition, nonresponse effects may turn any probability design into a nonprobability design if the characteristics of nonresponse are not well understood, since nonresponse effectively modifies each element's probability of being sampled.
Sampling methods may be either random (random sampling, systematic sampling, stratified sampling, cluster sampling) or non-random/nonprobability (convenience sampling, purposive sampling, snowball sampling). [3] The most common reason for sampling is to obtain information about a population.
This category is for techniques for statistical sampling from real-world populations, used in observational studies and surveys. For techniques for sampling random numbers from desired probability distributions, see category:Monte Carlo methods.
The sample is selected to approximately match the joint distribution of age, race, gender, and education in the 2016 American Community Survey (ACS). This is a purposive, rather than random, method of selection, designed to eliminate selection bias and non-coverage of the target population in the panel from which respondents were drawn.
Stratified purposive sampling is a type of typical case sampling, and is used to get a sample of cases that are "average", "above average", and "below average" on a particular variable; this approach generates three strata, or levels, each of which is relatively homogeneous, or alike. [1]
The number of childfree women is at a record high: 48 percent of women between the ages of 18 and 44 don’t have kids, according to 2014 Census numbers. The Huffington Post and YouGov asked 124 women why they choose to be childfree.