Sampling: An Overview
by Janet Salmons, PhD., Research Community Manager for SAGE Methodspace
Data collection is the Methodspace focus for Q2 of 2023. In order to collect or generate data, we need sources. We need a sampling strategy for determining which to include and exclude, and a recruiting strategy for finding them. While similar strategies are needed for locating and selecting documents or other types of sources, in this post we focus on human participants. Here we define basic terms for those new to research; in future posts we will go into more detail about the process of developing a sampling strategy, and the various approaches that can be used.
There are two broad types: probability and non-probability, also known as purposive sampling. Probability sampling is associated with quantitative research, and non-probability sampling is associated with qualitative research.
Probability sampling
The Encyclopedia of Research Design defines probability sampling as follows.
Sampling occurs when researchers examine a portion or sample of a larger group of potential participants and use the results to make statements that apply to this broader group or population. The extent to which the research findings can be generalized or applied to the larger group or population is an indication of the external validity of the research design.
Probability sampling is more likely to result in a representative sample and to meet the underlying mathematical assumptions of statistical analysis. The use of some kind of random selection process increases the likelihood of obtaining a representative sample. Simple random sampling is the most basic form of probability sampling in which a random number table or random number generator is used to select participants from a list or sampling frame of the accessible population. Stratified random sampling enables the researcher to divide the accessible population on some important characteristic, like geographical region. In this way, each of these stratum, or segments of the population, can be studied independently. Other types of probability sampling include systematic sampling and cluster sampling. (p. 1304)
Non-probability or purposive sampling
Qualitative Research Practice (2003) describes non-probability or purposive sampling:
The sample units are chosen because they have particular features or characteristics that will enable detailed exploration and understanding of the central themes and puzzles the researcher wishes to study. …Purposive sampling is preceisely what the name suggests. Members of a sample are chosen with a ‘purpose’ to represent a location or type in relation to a key criterion. (p.78-79)
Fritz, A., & Morgan, G. (Eds.) (2010). . (Vols. 1-0). SAGE Publications, Inc., https://doi.org/10.4135/9781412961288
Ritchie, J., Lewis, J., & Elam, G. (2003). Designing and selecting samples. In J. Ritchie & J. Lewis (Eds.), Qualitative research practice: A guide for social science students and researchers. Sage.
More Methodspace posts about data collection
Qualitative researchers often collect very personal data, whether in interviews or in narratives, diaries, or other records that depict their experiences. One way to protect their identities is by changing their names, and anonymizing the data.