Discussion: Sampling Theory

SAMPLING THEORY
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Sampling theory is a study that shows the relationship between a population and samples taken from the population. A population is a number of items that have similar characteristics. Sampling theory came about as a result of the need by researchers to come up with the most likely or most elaborate bit of the population that addresses a certain parameter which is under study. The theory therefore places much essence on the characteristic bits of the population such as the representation, elements and eligibility of the same. The popular sampling theories are simple random sampling, systematic sampling, convenience sampling, cluster sampling, and stratified sampling.
Analysis
Simple random sampling is the simplest of all the methods under sampling theory. Simple random sampling can be comparable to putting all items in population in one place; then, some are drawn. All items have an equal probability of being drawn, and it is used to avoid biases. However, this method has limitations because it is difficult to obtain all items in a population (Elwert and Winship, 2014). For example, in case the picked part of the sample contains a cluster of only one characteristic, there is a high chance of misrepresentation and hence wrong conclusions obtained. Convenience sampling is easy because the researcher uses the data from readily available items in the population. However, this data is unreliable because it can even provide biased information.
Systematic sampling is slightly similar to simple random sampling, only that, in this, a specified system for drawing samples from the population is used. For example, a list of items is counted off, and every nth item is chosen. In cluster sampling, the populace is divided into groups geographically. The groups are referred to as clusters. The clusters are randomly selected, and each item from the selected clusters...