Sampling Methods / Techniques: Probability vs Non-Probability Sampling
Sampling is one of the most important factors which determine the accuracy of your survey result. If the population under study is small, then there is a possibility to collect the data for each item or entity. But this is rarely the situation in survey research as most of the time the universe of population under study is tool large which necessitates the need to select a sample for the study. Sampling helps researchers to save time, energy, and money that require studying the whole population. It helps them to get inferences applicable to whole population with minimum resources.
Definition: Sampling is the process of selecting a representative group from the population under study with the intention of finding out a conclusion which can be applied to total population from which they were chosen. In short, it is the process of obtaining information about an entire population by examining only a portion of it. The method through which a sample is selected is known as ‘Sampling methods’. Let’s start with the understanding of basic terms in this context:
Population: The entire group of people or items that the researcher wants to study. It is denoted by ’N’ and alternatively known as ‘Universe’ also.
Sample: Samples are drawn from populations. The portion of the population, the researcher select for the study. It is denoted by ‘n’.
Sampling: The process of selecting a group of individuals from a population in order to study them and characterize the population as a whole.
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Sampling Methods / Techniques: Probability vs Non-Probability Sampling
Research Terms: An Annotated List of Useful Terms in Research