7.2.3 Sampling

Populations and samples

Population: refers to a large group of individuals that a particular researcher may be interested in studying. Often called a target population as it is a section of the general population.

• For practical and economic reasons, it is not possible to include all members of a target population, so a researcher selects a smaller group known as a sample.

• Ideally, the sample drawn will be representative of the target population to form generalisations. However, the majority of samples contain some degree of bias.

Technique	Evaluation
Random Sample • all members of the target population have an equal chance of being selected. To select a random sample; firstly, a complete list of all the members of the target population is obtained. Secondly, all participants are assigned a number. Thirdly, the sample is generated using a lottery method (computer-based randomiser or picking numbers from a hat).	Random sampling – free from researcher bias. The researcher has no influence over who is picked, this prevents them from choosing those who they think will support their hypothesis. However, it is difficult and time-consuming and a complete list of target populations is difficult to obtain. Still may end up with an unrepresentative sample. Selected participants may refuse to partake so the sample will become more like a volunteer sample.
Systematic sample – when every nth member of the target population is chosen – a sampling frame is produced, and a sampling system is selected to reduce bias. The researcher works through the sampling frame (selecting every nth participant) till they get a complete sample.	Systematic Sampling – avoids researcher bias as the researcher has no influence over who is chosen. Usually fairly representative.

| Stratified Sample – The composition of the sample reflects the proportions of people in certain sub-groups within the target or wider population. The researcher identifies the different strata that make up the population. Then the proportions required for the sample to be representative are worked out and then the participants making up each stratum are selected using random sampling. | Stratified sampling – avoids researcher bias, and produces a representative sample so findings are easier to generalise. However, the identified strata cannot reflect all the ways that people are different, so complete representation of the population is not possible. |

| Opportunity Sample – researchers select anyone willing and available at the time of the study. | Opportunity Sample – convenient, saves time and money. However, opportunity samples may be unrepresentative of the target population as it is drawn from a very specific area so findings cannot be generalised to the entire target population. Furthermore, the researcher has complete control over the selection of participants, so the sample is subject to researcher bias. | | Volunteer Sample – participants select themselves to be part of the sample. To select a volunteer, the researcher may place an advert in the local newspaper. | Volunteer sample – easy, minimum effort required, less time-consuming. Volunteer bias, however, attracts a certain profile of a person; someone who is keen and helpful (which then affects how far findings can be generalised). |