Why do you need a representative sample?
We turn now to consider why it is so important to make sure that your sample is representative of the study population. This is essential if you want to draw conclusions which are valid for the whole study population. This applies whenever you are conducting a quantitative survey, such as a cross-sectional, case-control or cohort study design. You can ensure that your sample is representative by using random selection of subjects from the population. Random sampling means sampling based on each individual in the population having the same chance (or probability) of being selected to be included in the sample.
Why do you think that it is important to make sure that the sample that you study is representative of all the people in your locality?
If the sample is not representative then you will not be able to say anything about the rest of the community. You will just have studied a number of people from your community, but they will not necessarily represent the community as a whole.
For qualitative data it is not necessary to ensure that your sample is representative, because the purpose of the research is to learn about those individuals specifically, and their knowledge, beliefs and practices. Therefore, samples for qualitative research studies are usually selected using non-probability sampling methods.
Next we will describe probability and non-probability sampling methods in detail, so you can see different methods of deciding how the members of your sample will be selected (sampling methods) and how many individuals must be included (sample size).