What Are The Disadvantages Of Purposive Sampling?

• The Definition of Purposive Sampling.

As defined by Kerlinger (1986), purposive sampling is another non-probability based sampling. It is characterized by a deliberate effort to obtain representative samples through the inclusion of groups or typical areas in a sample. It avoids random sampling by targeting a specific group of people, often a small group rather than a more general one. It can help where groups are too small to be selected through general, random sampling.

• Disadvantages of Purposive Sampling.

The selection criteria the researcher uses can be very arbitrary and are almost always subjective. The narrowness of the questions used will reflect the researcher's particular stance on a subject far more than a random sample.

The sample population used may not necessarily be entirely the population that the researcher is trying to reach. As such, since such a small sample population is often used, a small variation in the sample will cause deviance in the results. The size of the purposive sample makes the result far more sensitive.

With probabilistic sampling, the general probability or odds of a good representation of the population are well established and known. With non-probability data, the general population may not be sampled correctly. It may be harder to evaluate what has actually been achieved since purposive sampling can be so subjective.

At least with a probabilistic sample, we know the odds or probability that we have represented the population well. We are able to estimate confidence intervals for the statistic. With non-probability samples, we may or may not represent the population well, and it will often be hard for us to know how well we've done so.

Due to the narrow range of the purposive sample, it is possible to put undue weight on the data obtained purely because the sampling is so small.