Analyzing and Understanding the Techniques Used in Sampling

¶ … employing convenience samplings is some bias in non-representative population. Due to this limitation, convenience sampling is not usually subject to tight sample measures (Bailey, 2009). Convenience samples don't give the representative outcome. If a person needs to extend the targeted population, convenient samples cannot acquire the research there. The normal instinct is to extract from the convenience samples. When using convenience samples, there is the likelihood to handle the results as representational, though they may not be. The outcome of convenience samples is difficult to clone. If a researcher conducts the analysis of a convenience survey outcome by means of a list source, they would often observe dramatic variations in the feedback from the various lists, usually in a manner that would complicate the explanation (Convenience Samples: Pros and Cons, 2010).

Although convenience samples are way better than having no samples entirely, the limitations of the convenience samples must be observed and recognised when a researcher is interpreting the findings of a study. In a small or seemingly inadequate sample, the ills of generalization have severe impact on the population that is being studied (Grinnell & Unaru, 2007). A convenience sample usually suffers from numerous biases. Given an example, a convenience sample might cause over-representation or under-representation of some groups in the sample. The sample may not be an accurate representation of the population in study, because the frame of the sampling is unknown, and this sample was not randomly chosen. This, as a result, lowers a researcher's capability to come up with generalizations from the population sample being studied (Mugera, 2013).

Due to the high chances of self-selection in a non-probability instance of sampling, the consequences of outliers may be more frustrating in this subject selection type. Cases which are not considered as part of the data are outliers. On the contrary, biases and their chances are not quantified in a convenience sample. Actually, a researcher is not aware of how accurate a convenience sample will be at representing a population concerning the mechanisms or traits being researched. Convenience samples are very unpredictable because they are vulnerable to severe concealed biases (Etikan, Musa and Alkassim, 2016).

A sample is a representation of events, items or people from a much bigger population from which a researcher, gathers and observes, to draw conclusions (What is the dissimilarity between a sample and a population? n.d). In a population of 500, the study sample would be 8 individuals. A sample should be a representation of the population it got drawn from and should be sizeable enough to validate statistical analysis. The duty of the sample is to allow for the sample from the population to be studied by the researcher, and to derive inferences that would be applicable to the rest of the population. It is more or less a give-take situation, where a sample is given by the population and then the population takes inferences from the obtained results (Population Sampling Techniques, n.d).

Factors to Consider in Sampling

Sampling cost (the value of the information) -- because sampling cost helps to decide how accurate our estimates are to be.

Prior information- because should there be any previous information from a previous study in the process, the information would be used to cut down the sizes of the samples.