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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.
A judgment sample, or expert sample, is a type of non-random sample that is selected based on the opinion of an expert.. Results obtained from a judgment sample are subject to some degree of bias, due to the sample's frame (i.e. the variables that define a population to be studied) and population not being identical.
The most common form of systematic sampling is an equiprobability method. [1] This applies in particular when the sampled units are individuals, households or corporations. When a geographic area is sampled for a spatial analysis , bi-dimensional systematic sampling on an area sampling frame can be applied.
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.
In statistics, survey sampling describes the process of selecting a sample of elements from a target population to conduct a survey. The term "survey" may refer to many different types or techniques of observation. In survey sampling it most often involves a questionnaire used to measure the characteristics and/or attitudes of people.
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.
A simple illustration of aliasing can be obtained by studying low-resolution images. A gray-scale image can be interpreted as a function in two-dimensional space. An example of aliasing is shown in the images of brick patterns in Figure 5. The image shows the effects of aliasing when the sampling theorem's condition is not satisfied.