/    /  Statistics – Convenience Sampling

Convenience Sampling:

A non-probability sampling technique in which subjects are selected because of their convenience. The convenience samples are also called as the Accidental Samples because the subjects happen to be accidentlyselected under study.This method is also referred as the chunk (fraction) taken from the population on the basis of its convenient availability and accessibility to the investigator.

Facebook pollsis a popular example for convenience sampling.Some of the convenience samples which are available readily are the telephone directory, census survey report, automobile registration list and so on.

In pilot studies, the researcher prefers convenience sample because it allows to obtain basic data and trends regarding his study and also to avoid the complications of a randomized sample.This sampling technique is useful in documentation that a particular quality or phenomenon occurs within a given sample.

When using convenience sampling, it is necessary to describe how the sample differs from an ideal random sample.Description of the individuals who might be left out during the selection process or the individuals who are overrepresented in the sample might also be necessary.

In business studies, this method is used to collect initial primary data regarding specific issues such as perception of image of a particular brand or collecting opinions of perspective customers to a new design of a product.

Advantages:

Ease of research and simplicity of sampling

Helps in pilot studies and for hypothesis generation

Data collection can be facilitated within short duration of time due to its simplicity.

Disadvantages:

Risky due to selection bias and influences beyond the control of the researcher. The best way of reducing bias is using it along with probability sampling. Since probability sampling gets the measurement parameter with it to keep the bias under check.

High level of sampling error since the samples are selected conveniently, it is not necessary that these reflect the true attributes or characteristics of the target population. Also, there are several choices of bias of the investigator’s selection which can tamper the results that leads to higher level of sampling error.