/    /  Statistics – Quota Sampling

Quota Sampling:

A non-probability sampling technique where the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics.The main reason in choosing quota samples is that it allows the researchers to sample a subgroup that is of great interest to the study.

In a study that considers gender, socioeconomic status and religion as the basis of the subgroups, the final sample may have a skewed representation of age, race, educational attainment, marital status and a lot more.

Quota sampling can be classified as: controlled and uncontrolled.

Controlled quota sampling involves certain restrictions in order to limit sample choice of researcher.

Uncontrolled quota sampling, on the other hand, does not have any restrictions.

Step-by-step Quota Sampling:

The first most step is to bifurcate the entire population into mutually exhaustive subgroups, i.e., the elements of each of the subgroups should be a part of only one of those subgroups.For example, if a researcher wishes to understand the target market for an upcoming Bluetooth headphones variant, the most precise quota characteristic will be according to age groups.

The researcher then evaluates the proportion in which the subgroups exist. This proportion has to be maintained within the sample selected using this sampling method.If 58% of the people who are interested in purchasing Bluetooth headphones are between the age group of 25-35 years, your subgroups also should have the same percentages of people.

Selecting the sample size while maintaining the proportion evaluated in the previous step. If the population size is 500, the researcher can select a sample size of 50 elements.

Advantages of Quota Sampling:

Time effective since the primary data collection can be done in shorter time.

Cost-effective.

Independent on the presence of the sampling frames.

Disadvantages of Quota Sampling:

Calculating the sampling error is not possible in non-probability sampling methods.

The riskyprojection of the research findings to the total population.

Other characteristics may be disproportionately present in the final sample group.

Great scope for researcher bias and the quality of work depends on researcher’s experience.