In random sampling, each member of the population studied would get an equal chance
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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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