Sampling can be basically categorized into probability and non-probability sampling. In probability sampling, each and every element of the population has a probability of being selected in the sample, i.e., the probability can be accurately measured. Whereas, in non-probability sampling, not all elements have a chance of being selected in the sample, i.e., their probability cannot be accurately measured.
The commonly used sampling methods are given below:
» Deliberate sampling: It is a non-probability sample design in which the researcher purposively or deliberately selects certain units of the universe to form a sample that would represent the universe. In other words, it is a sampling with a purpose. It is also known as purposive sampling.
» Simple random sampling: It is a probability sample design where each and every element has an equal probability of being selected in the sample. It is also known as chance sampling.
» Systematic sampling: In this method, elements from a large population are selected at periodic intervals according to a random starting point, i.e., every nth element is selected for the sample, where n can be any random position of an element.
» Stratified sampling: In this method, the researcher divides the entire population into different subgroups or strata, and then randomly selects elements proportionally from the strata to include in the sample.
» Quota sampling: It is a non-probability sample in which the researcher selects random units for a sample according to certain given criteria or quota. In other words, elements are selected according to pre-specified criteria in such a way that the sample represents the same characteristics of the population under study.