SAMPLING METHODS

Sampling Methods

Sampling Methods

Difference between Probability and Non Probability Sampling Methods

Probability sampling entails selecting a sample from a population, selection based on the principle of randomization. It is more complex, takes longer and is usually more expensive than the non-probability sampling. However, as the population units are selected at random and it is possible to calculate the probability of inclusion of each unit in the sample, one can, with probability sampling, produce reliable estimates, as well that estimates of sampling error and make inferences about the population (Burns, Grove, 2007, 56-64). Probabilistic methods are those based on the principle of equi-likelihood. That is, those in which all individuals are equally likely to be selected to be part of a sample and therefore all possible samples of size n have the same probability of being chosen.

In the case of non-probability sampling, since the researcher are chosen arbitrarily, there is no way to estimate the probability of any one element be included in the sample. Also, as the method in question provides no assurance that each item has a chance of being included in the sample, one can estimate the sampling variability or to identify bias as possible (Neuman, 2005, 26-34).

Forms of Sampling

Random Sampling

Random sampling is selected at random and each member has an equal chance of being included.

Cluster Sampling

This technique is useful when the universe or the required study population is subdivided into smaller universes or populations with similar characteristics to the universe or population. The researcher proceed to divide the population into a finite number of clusters and, between them, is passed to elect some to be the only ones to be investigated, this election may be made by the method of simple random or systematic by chance; once this stage can be affected within each of the clusters ...