Vocabulary list: Sampling procedures

Sample: A sample is a subsection of research participants selected from a larger group of research interest. If the sample is selected in a scientific way, the results obtained for the sample can then be generalised to the larger group of research interest, called the population.

Representative sample: A sample that is approximately the same as the population from which it is drawn in every important participant characteristic. There are different ways of obtaining a sample that is considered to be representative. Two ways are called random sampling and stratified sampling.

Random sampling: A sample procedure that ensures that every member of the population of research interest has a genuinely equal chance of being selected as a participant for the research study. An example of obtaining a list of all the people in the population is called a sampling frame. For example, an electoral roll or telephone numbers of all the people in the particular location may be used.

Stratified sampling: It involves dividing the population to be sampled into different subgroups or strata (area, age, sex, income level, ethnic or cultural backgrounds) then selecting a separate sample from each subgroup (called stratum) in the same proportions as they occur in the population of interest.

Random-stratified sampling: When random sampling is used to select a sample from each stratum, it is called random-stratified sampling. To obtain a random stratified sample, the researcher must obtain accurate lists of all the people within each stratum, and then the researcher will draw a random sample of proportionate size from each of the strata.

Random allocation: Participants selected for the experiment are just as likely to be in the experimental group as the control group. This means that every person who will be a participant in the experiment has an equal chance of being selected in any of the groups...