A sample that is obtained by determining the sampling interval (i.e., the population size divided by the desired sample size, N/n, which is symbolized by k), selecting at random a starting point (a number between 1 and k, including 1 and k), and then selecting every kth element in the sampling frame. It uses a different strategy for selecting the elements to be included in the sample. It is generally easier than simple random sampling when you are selecting from lists.
a set of elements taken from a larger population according to certain rules.
the basic unit selected form the population.
the set of all elements; the large group to which a researcher wants to generalize his or her sample results; the total group that you are interested in learning more about. Sometimes called target population.
Numerical characteristic of a sample.
Numerical characteristic of a total population.
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a technique in which a population is divided into mutually exclusive groups (called strata) and then a simple random sample or a systematic sample is selected from each group (each stratum).
Proportional Stratified Sampling
requires fewer people than simple random sampling, making it more efficient. The proportions in the sample on the stratification variable will be perfectly or almost perfectly representative of the proportions of that same stratification variable in the population.
Disproportional Stratified Sample
Often used when the research interest lies more in comparing groups that in making generalizations about the total population. In this sampling, you would select individuals disproportional to their occurrence in the population.
a form of sampling in which a collective type of unit that includes multiple elements, such as schools, churches, classrooms, universities, households, and city blocks, rather than single-unit elements such as individual students, teachers, counselors, and administrators are randomly selected.
One-stage cluster sampling
a set of clusters is randomly selected from the larger set of all clusters in the population.
Two-stage cluster sampling
a random sample of elements is drawn from each of the clusters selected in stage one.
used when researchers include in their sample people who are available or volunteer or can be easily recruited and are willing to participate in the research study.
The researcher identifies the major groups or subgroups of interest, determines the number of people to be included in each of these groups, and then selects a convenience sample of people for each group.
the researcher specifies the characteristic of a population of interest and then tires to locate individuals who have those characteristics. Sometimes called judgmental sampling.
Each research participant who volunteers to be in a research study is asked to identify one or more additional people who meet certain characteristics and may be willing to participate in the research study.