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Sampling Methods


Before an organisation conducts primary research it needs to pick a list of people/organisations to interview. You can not interview the whole population; that would be expensive and probably impossible. Instead if you want to conduct research which involves interviewing people, you will need to select a group of people to interview. There are a number of ways to select the sample of people to be interviewed; this article covers probability sampling and non-probability sampling.

The diagram below summarises probability and non-probabaility sampling methods.

Sampling Methods Diagram

Probability Sampling Methods

Probability sampling methods are said to be mathematical ways to select the group of people that will be interviewed. They are known as probability sampling methods because each person in the group from which the sample will be selected has a "known" chance (probability) of being selected. There are three probability sampling methods: Simple random samples, systematic samples and multi-stage samples.

Simple Random Samples

Simple random sampling involves making a list of the people from which the sample of respondents (people that will be interviewed) is selected. For example a group of 100 are listed and a group of 20 may be selected from this list at random. The selection may be done by computer or by hand.

Systematic Samples

Just like simple random sampling, systematic sampling involves drawing up a list of potential respondents. The next stage is to decide what system will be used to select the respondents from the list. For example every 5th person on the list will be selected as a respondent so that would be the 5th, 10th, 15th, 20th person and so on. Similarly if the interviewers implement a 10th person system, they would choose the 10th, 20th, 30th, 40th, 50th person and so on.

Multi-Stage Samples

With this sampling process the respondents are chosen through a process of defined stages. For example residents within Islington (London) may have been chosen for a survey through the following process:

Throughout the UK the south east may have been selected at random, ( stage 1), within the South East London is selected again at random (stage 2), Islington is selected as the borough (stage 3), then polling districts from Islington (stage 4) and then individuals from the electoral register (stage 5). As demonstrated five stages were gone through before the final selection of respondents were selected from the electoral register.

Non-Probability Sampling Methods

Convenience Sampling

Where the researcher questions anyone who is available. This method is quick and cheap. However we do not know how representative (of the population) the sample is and how reliable the result. It is down to the researcher to ensure that they pick a people with a large variety of characteristics.

Quota Sampling

Using this method the sample respondents are made up of potential purchasers of your product or the market that you would like to research. The sample will contain people who meet certain criteria e.g. age, social group, gender. Splitting the sample into age is a popular way to apply quota sampling, the researcher will be asked to interview a set number (quota) of people from different age groups e.g. 16-25, 25-40, 40-55, 55 and above. Quota sampling ensures that the sample contains people satisfying all of the characteristics in the market being researched.

Dimensional Sampling

Dimensional sampling is an extension to quota sampling. The researcher takes into account several characteristics e.g. gender, age, income, residence and education. The researcher must ensure that there is at least one person in the study representing each of the chosen characteristics. For example out of 10 people the researcher ensures they have interviewed 2 people that are a certain gender, 2 a certain age group and 2 who have an income between £25000 and £30000.


To summarise there are two types of sampling frames - probability and non-probability. The most suitable method will depend on the researcher's aims, resources and time scales.


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