In random sampling, each member of the population studied would get an equal chance to be selected as a subject in the sample. This unique feature of random sampling enables the researcher to obtain a sample which represents all qualities of the study populationcomprehensively. In addition, random sampling also eliminates researcher bias (Grove, 2007).

By increasing the representation of the sample, random sampling also increases the generalizability of the study findings. Based on such a good sample, the researcher can also make out inferences about the larger population (Middleton, 2010).

In actual practice, obtaining a truly random sample is a tough task because of many barriers. Unavailability of selected respondents, refusal to participate, low response rate, etc are some of the barriers to obtaining a truly random sample. Obtaining a comprehensive list of all the individuals of the population studied is also a barrier to truly random sampling (NEDARC, 010). To overcome the barriers to truly  random sampling, an opportunistic sample can be selected than a truly random sample.

An opportunistic sample would be the one which is obtained by random sampling, but from a pool of individuals of the population who are accessible (Angrosino, 2010). Thus, by having a good knowledge about the characteristics of the population from which the sample is drawn, the researcher can prevent sampling errors and bias to a great extent (Baneerjee & Chaudhury, 2010).

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