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‘A sample is a finite part of a statistical population whose properties are studied to gain information about the whole’ (Webster, 1985).

1.2 Sampling techniques

There are two main types of sampling: probability and non-probability sampling.

Probability sampling

A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, researchers must set up some process or procedure that assures that the different units in their population have equal probabilities of being selected. Probability sampling is divided into:

Simple random sampling – it is the basic sampling technique, where a group of subjects (a sample) for study are selected from a larger group (a population). Each individual is selected totally by chance and each member of the population has an equal chance of being included in the sample.

Stratified sampling – population is divided into subgroups (strata) and members or units are randomly selected from each group

Systematic sampling – uses a specific method to select members or units e.g. every 10th person on an alphabetized list

Cluster random sampling – divides the population into clusters. Clusters are randomly selected and all members of the cluster selected are sampled

Multi-stage random sampling – a combination of one or more of the above methods is applied

Non-probability sampling

A basic characteristic of non-probability sampling techniques is that samples are selected based on the subjective judgement of the researcher, rather than random selection (i.e., probabilistic methods). Non-probability sampling is divided into:

Convenience or accidental sampling – members or units are selected based on availability

Purposive sampling – members of a specific group are purposefully selected to participate in the study

Modal instance sampling – members or units are the most common within a defined group and therefore are sought after

Expert sampling – members considered to be of high quality are selected for participation

Proportional and non-proportional quota sampling – members are sampled until exact proportions of certain types of data are collected or until sufficient data in different categories is obtained

Diversity sampling – members are selected intentionally across the possible types of responses to capture all possibilities

Snowball sampling – existing study subjects recruit future subjects from among their acquaintances, and this process continues until enough subjects are collected

Table 1.

Probability and Non-probability Sampling

Table 2.

Key Differences between Probability and Non-probability Sampling

References

Bryman, A., & Cramer, D. (1994). Quantitative data analysis for social scientists (rev. Taylor & Frances/Routledge.

Creswell, J. W. (2002). Educational research: Planning, conducting, and evaluating quantitative. Prentice Hall.

Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications, Incorporated.

Additional Reading: