Note: Please use readings and other sources for
a more complete discussion.
Probability Sampling: subjects are selected in
such a way that every member of the population actually has a possible
chance of being selected.
Type of Probability Sample Designs:
Simple Random: each member of the study population has an equal chance of being selected.
Systematic sampling: each member of the study population is either assembled or listed, a random start is designated, then members of the population are selected at equal intervals.
Stratified: each member of the study population is assigned to a group or stratum, then a simple random sample is selected from each stratum.
Cluster: each member of the study population is assigned to a group or cluster, then clusters are selected at random and all members of a selected cluster are included in the sample.
Multi-stage: clusters are selected as in
the cluster sample, then sample members are selected from the cluster members
by simple random sampling. Clustering may be done at more than one
subjects are selected based on the judgment of the researchers to achieve
particular objectives of the researcher.
Types of Non-probability Sample Designs:
Convenience: select cases based on their availability for the study.
Example: Psychologists interested in the relationship between violence in movies and aggressive behavior by the American public may use student volunteers to participate in an experiment. One group is shown a movie without violence, the other group is shown a movie with graphic violence. Then both groups are observed and interviewed.
Age and level of stress of college student's may affect the findings.
Most Similar/Dissimilar: Select cases that are judged to represent similar conditions, or alternatively, very different conditions.
Example: Case studies of nations such as U.S. and
France, to contrast the worst and best case of a policy issue.
Typical case sampling: Select cases that are known beforehand to be useful and not be extreme
Example: Select a few cases that are said to be
normal or usual. For example, selecting Chicago and New York to study
their recycle program to represent major cities in general. Need
to scrutinize researchers selection of cases.
Critical: Select cases that are key or essential for overall acceptance or assessment.
Example: predicting election results - "As Maine
goes, so goes the nation"
Snowball: Group members identify additional members to be included in sample.
Example: illegal drug users, illegal aliens
Quota: Interviewers select sample that yields the same proportions as the population proportions on easily identified variables.
Example: The researcher divides population group being studied into subgroups : male, female , black , white. In quota sampling, the interviewer is left with the discretion of selection. Ex. Interviews conducted in shopping malls.
Utility of Non-probability samples:
studies of special populations; exploratory research in attempting to see
if a problem exists; a small pilot study may help to know whether you should
pursue research further.