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INTRODUCTION
A sample refers to a smaller, manageable version of a larger group. It is a subset containing the characteristics of a larger population. Samples are used in statistical testing when population sizes are too large for the test to include all possible members or observations.
A sample should represent the population as a whole and not reflect any bias toward a specific attribute.
A population is the total number of individuals, animals, items, observation, data, etc. of any given subject. It is a portion, part, or fraction of the whole group, and acts as a subset of the population.
Sampling is defined as the process of selecting certain members or a subset of the population to make statistical inferences from them and to estimate characteristics of the whole population.
Importance of sampling
Using whole populations for research comes with challenges, which is why samples are used. Researchers may have problems gaining ready access to entire populations. And because of the nature of some studies, researchers may have difficulties getting the results they need in a timely fashion. This is why people who conduct studies use samples.
Using a smaller number of people who represent the entire population can still produce valid results while cutting back on time and resources. Samples and sampling methods are widely used in a variety of settings where research is conducted. It is also a time-convenient and a cost-effective method and hence forms the basis of any research design. Samples used by researchers should closely resemble the population. All the participants in the sample should share the same characteristics and qualities.