Explain sampling and its two techniques

Understanding sampling is crucial. We'll delve into two key techniques: probability sampling, which ensures every member of the population has an equal chance of being selected, and non-probability sampling, which uses targeted methods to reach specific subgroups.

Now, let’s move on to the concept of sampling.

Unlike a census or poll (where all members of the population are studied), surveys gather information from only a portion of the population of interest – the size of the sample will depend on the purpose of the study (we will discuss this issue later).

In a good survey, the sample is not selected randomly or only from persons who volunteer to participate. It is scientifically chosen so that each person in the population will have a measurable chance of being selected. This procedure is called sampling. This way the results can be reliably projected from the sample to the larger population.

There are two important key words involved in sampling and they are population and sample. The word population is defined as all people, objects or events found in a particular group that the researcher is planning to generalise on (Borg & Borg, 1983).

There are two types of sampling techniques:

Two Types of Sampling Techniques