What is meant by sampling?
Sampling is the process of selecting a number of study subjects from a defined study population (i.e. the population being investigated). In most research projects it is not possible to include all the study population in the research design. Therefore, you need to look at a sample of individuals who will give you the necessary information that you can then apply to everyone in the study population. As you have already learned, it is first necessary to define the study population being investigated and only then can you begin to think about how you might take a sample from it.
Why do you think that sampling may be necessary if you want to study health issues in your locality?
If it is not possible to study everybody in your locality, a representative sample of people has to be studied.
As you have learned in previous study sessions, study variables can be categorised as quantitative and qualitative, and the data you collect in a research study may also be categorised in this way. Your sampling methods should follow different techniques depending on whether the data is quantitative or qualitative. In this section you will learn about sampling methods for both types of data, and also how to avoid bias in the sampling process.
How might bias arise in data collection?
Bias means that data is distorted in some way. This may happen if you are collecting data by interview and you prompt respondents to make particular answers. It can also happen if you 'hand pick' your study subjects, for example, by only choosing people who live nearby or people you know.