Sampling

Question	Answer
sampling	The process of drawing a number of individual cases from a larger population.
element	A kind of thing a researcher wants to sample.
population	The group of elements from which a researcher samples and to which she or he might like to generalize.
sample	A number of individual cases drawn from a larger population.
target population	The population of theoretical interest.
sampling frame/study population	The group of elements from which a sample is actually selected.
non probability samples	Samples that have been drawn in a way that doesn't give every member of the population a known chance of being selected.
probability samples	Samples drawn in a way to give every member of the population a known (nonzero) chance of inclusion.
biased samples	Samples that are unrepresentative of the population from which they've been drawn.
generalizability	The ability to apply the results of a study to groups or situations beyond those actually studied.
coverage error	An error that results from differences between the sampling frame and the target population.
nonresponse error	An error that results from differences between non responders and responders in a survey.
sampling error	Any difference between sample characteristics and the equivalent characteristics in the sampling frame, when this difference is not due to nonresponse error.
parameter	A summary of a variable characteristic in a population.
statistic	A summary of a variable in a sample.
random-digit dialing	A method for selecting participants in a telephone survey that involves randomly generating telephone numbers.
sampling variability	The variability in sample statistics that can occur when different samples are drawn from the same population.
simple random sampling	A probability sample in which every member of a study population has been given an equal chance of selection.
sampling distribution	The distribution of a sample statistic (such as the average) computed from many samples.
margin of error	A suggestion of how far away the actual population parameter is likely to be from the statistic.
systematic sampling	A probability sampling procedure that involves selecting every "kth" element from a list of population elements, after the first element has been randomly selected.
stratified random sampling	A probability sampling procedure that involves dividing the population in groups or strata defined by the presence of certain characteristics and then random sampling from each stratum.
cluster sampling	A probability sampling procedure that involves randomly selecting clusters of elements from a population and subsequently selecting every element in each selected cluster for inclusion in the sample.
multistage sampling	A probability sampling procedure that involves several stages, such as randomly selecting clusters from a population, then randomly selecting elements from each of the clusters.
purposive sampling	A non probability sampling procedure that involves selecting elements based on the researcher's judgment about which elements will facilitate his/her investigation.
quota sampling	A non probability sampling procedure that involves describing the target population in terms of what are thought to be relevant criteria and then selecting sample elements to represent the "relevant" subgroups in proportion to their presence in the target population.
snowball sampling	A non probability sampling procedure that involves using members of the group of interest to identify other members of the group.
convenience sample	A group of elements that are readily accessible to the researcher.

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	Created by Caitlin Hall about 8 years ago