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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 population

comprehensively. 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,

2010). 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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