The teacher then places the numbers in a jar and

The teacher then places the numbers in a jar and draws out one at a time until the desired total number
is reached.
These are all examples of probability sampling designs, except for (1) the researcher who recruits four
subjects and asks each to invite or identify other people who might meet the criteria for participation in
the study, and (2) the researcher who concurrently collects, codes, and analyzes data and decides what
data to collect next and from which potential participants to collect them, in order to develop the
emergent theory. The former is an example of network sampling, which is nonprobability (nonrandom)
sampling. Network or snowball sampling is a technique in which existing study subjects recruit future
subjects from among their acquaintances. Thus, the sample group is said to grow like a rolling snowball.
As the sample builds up, enough data are gathered to be useful for research. This sampling technique is
often used in hidden populations that are difficult for researchers to access. The latter is an example of
theoretical sampling, which is nonprobability sampling and commonly used in grounded theory
qualitative research. The researcher gathers data from any individual or group that can provide relevant
data for theory generation. The data are considered relevant if they include information that generates,
delimits, and saturates the theoretical codes in the study needed for theory generation. A code is
saturated if it is complete and the researcher can see how it fits in the theory. The researcher continues
to seek sources and gather data until the codes are saturated and the theory evolves from the codes and
the data. Diversity in the sample is encouraged so that the theory developed represents a wide range of
behavior in varied situations.
The researcher determines a characteristic that varies within the population and that is essential to
include in the sample, in all its forms. The researcher divides the population into smaller groups, each
containing one form of the characteristic, and then randomly selects from each group.
These are all examples of probability sampling designs, except for (1) the researcher who recruits four
subjects and asks each to invite or identify other people who might meet the criteria for participation in
the study, and (2) the researcher who concurrently collects, codes, and analyzes data and decides what
data to collect next and from which potential participants to collect them, in order to develop the
emergent theory. The former is an example of network sampling, which is nonprobability (nonrandom)

sampling. Network or snowball sampling is a technique in which existing study subjects recruit future
subjects from among their acquaintances. Thus, the sample group is said to grow like a rolling snowball.