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Section 4: THE RIGHT TOOLS TO MANAGE THE JOB
Step Fourteen: What is the sampling frame for my project?
It is important that you give some consideration to how the researcher might sample or select from the subjects or objects of your research project.
The entire group of subjects or objects which is the focus of your research project (for example, museum volunteers in the South West or cultural businesses in the South West) is known as the population. A sampling frame is created by listing all members of the population.
You must decide whether it is feasible or desirable to try to consult them all, a census , or whether you want to select a sample.
Some sampling frames are easy to identify and consult as a whole census, while others are either more difficult to identify or too numerous to consult as a group and, therefore, you will need to select a sample of that population to participate in your research.
Health Warning: Beware that sampling frames can be incomplete or inaccurate. For example, when counting the number of cultural businesses in the South West region there are business registers such as the Inter-departmental Business Register which is a list of businesses maintained by the National Statistics. It can be used to produce lists of businesses, i.e. a sampling frame, but it is important to note that it misses some very small businesses (self-employed and those without employees and low turnover) and some non-profit making organisations.
Samples can reflect the populations from which they are drawn with varying degrees of accuracy. A sample which accurately reflects its population is called a representative sample. A sample which is not representative of its population is described as biased.
There are a wide variety of sampling strategies available for use. They are divided into two groups, probability and non-probability sampling.
| Sampling Strategies |
Probability sampling
- Simple random sampling – selection at random
- Systematic sampling – selecting every nth case
- Stratified sampling – sampling within groups of the population
- Cluster sampling – surveying whole clusters of the population sampled at random
- Stage sampling – sampling clusters sampled at random |
Non-probability sampling
- convenience sampling – sampling those most convenient
- voluntary sampling – the sample is self-selected
- quota sampling – convenience sampling within groups of the population
- purposive sampling – hand-picking supposedly typical or interesting cases
- snowball sampling – building up a sample through informants |
| Source: Blaxter, L., Hughes, C. & Tight, M. (1996) How to Research, Buckingham: Open University Press. |
A probability sample is one in which each individual or object in the population of interest has an equal, or at least known, chance (probability) of being selected.
A non-probability sample is one in which some individuals or objects have a greater, but unknown, chance than others of selection.
Non-probability sampling strategies are used when a sampling frame of the population in question does not exist or where probability sampling strategies are not deemed necessary. Market researchers commonly use a quota sampling approach with targets for the numbers they have to interview with different socio-demographic characteristics.
More information on sampling can be found in A Practical Guide to Sampling and in Appendix 1 of Commissioning market research: a guide for arts marketers.
Top tip: there are circumstances where you, as the commissioner, will be in a better position to identify the sample for participation in your research project because of your local networks, knowledge and contacts (this may be the case particularly for the collection of qualitative data, where a sample frame is harder to identify).
Health Warning: be selective when it comes to setting up interviews and allow sufficient time to coordinate busy diaries. Chief executives, for example, are likely to be booked up well in advance. So be realistic. Do not expect any of them to available within the Next Page week or two - plan ahead!
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