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Sampling Methods:

Random: In a random sample every member of the target population has an equal chance of being selected for the sample. This means that the researcher must identify all the members of the target population, number each person and then draw out the required number of people. If the target population is small, then all the numbers can go into a hat to be drawn out. If it is large, then a computer programme can be used to do this. This sampling method is fair and not biased because the researcher cannot choose the individual participants.

Opportunity: Choosing people who are members of the target population and are available and willing to take part. Often these people are friends of the researcher so they may not represent the target population very well. This could produce and biased sample. However it is a quick and easy way to collect people for a study.

Systematic: systematic sampling involves selecting every nth member of the target population. For example, if the researcher decides that 'n' will be '7', every 7th person in the target population is selected. This is unbiased because the researcher cannot choose the individuals.

Stratified: In stratified sampling, the researcher must identify the subgroups in the target population and work out what proportion of that target population each group represents. For example, in a school there are several subgroups: teachers, other staff, students in each year, and so on. If the teachers make up 10% of the whole school target population then 10% of the sample must be teachers. This is repeated for each subgroup. Once the researcher knows what proportion needs to be selected for the sample, a random sample of each subgroup is taken. This is very time-consuming. However, it will provide an unbiased and very representative sample of people for the study.