Probability sampling methods
Probability sampling involves using random selection procedures to ensure that each member of the sample is chosen on the basis of chance. All members of the study population should have an equal (or at least a known chance) of being included in the sample. For example, names drawn out of a hat or computer-generated random numbers are random selection methods. A probability sampling method is a process that protects your research from bias and ensures that you have a representative sample. Furthermore, it will help you to make meaningful statistical estimations when you analyse the results of your research.
Why do you think that random selection of people for your sample is so important?
If the sample selection is not done in a random manner, then the sample will not be representative of the rest of the community. It will probably include a bias in the selection, i.e. too many or too few people will be included who are not representative of the population as whole.
Probability sampling requires that a list of all study population members exists or can be compiled. This list is called the sampling frame. The following probability sampling methods will be discussed here:
- Simple random sampling
- Systematic sampling
- Stratified sampling.