The Advantages and Disadvantages of Quota Sampling Compared to Random Sampling

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Introduction

The Advantages and Disadvantages of Quota Sampling Compared to Random Sampling Introduction Quota sampling is a non-probability sampling method, compared to random sampling methods, which are known as probability sampling methods. Examples of probability methods are stratifying sampling, cluster sampling, systematic sampling and simple random sampling. When a sample needs to be taken from a population, the issue of which type of sampling method to use arises; probability or non-probability. Since we are looking at specifically quota sampling, we need to define it. Quota sampling involves stratifying a population into mutually exclusive sub-groups, as if using the stratified sampling method. However, the difference is, in quota sampling, judgement is used instead of randomness to select units from each stratum. The number of sampling units chosen from each stratum is based on proportion. Random sampling is defined as when every unit in the population has a probability of being chosen. For a random sample to be carried out, there also needs to be a sampling frame. Advantages of Quota Sampling Although quota sampling is criticised heavily by academics, it does have its advantages. The biggest case for it is that is incredibly cheap to carry out.

Middle

This limitation means that results taken from a random sample have more potential for statistical analysis as opposed to quota sampling. Another disadvantage of quota sampling is that most of the time, the sample will be divided into economic/social class groups. If the judgement of who belongs to which class is left completely up to the interviewer, then there is potential for bias. There is no statistical theory based on dividing a population according to economic/social class, so results can be difficult to interpret. There is also the possibility of differing opinions of class between the interviewers if there are more than one working on the sample, therefore inferences made from the sample will have to be made very carefully (Moser & Stuart, 1953). We have to also consider the possibility of bias erupting within the quotas at an individual level, leading to misrepresentations of the population. Take for instance; there is a quota for over 60 year olds. If the interviewer only finds people who range from 60 years old to around 65, then there is no representation of people who much older than 65 (Moser & Stuart, 1953).

Conclusion

The Washington State Public Opinion Laboratory also carried out its own polls separately before the election using both probability sampling and quota sampling: The Washington state poll of 1948 Candidate Actual Washington state vote Probability Sample Quota Sample Dewey 42.7 46.0 52.0 Truman 52.6 50.5 45.3 Wallace 3.5 2.9 2.5 Source: Scheaffer, Mendenhall Lll, Lyman Ott : Elementary Survey Sampling, page 15 An article of the Journal of the Royal Statistical Society included a study where a random sample and a quota sample were carried out simultaneously to compare the results after, and see which method gave the most precise result. The conclusion of the study was that there was not any significant difference between the results of the two sampling methods, and that academics have too easily made quota sampling a redundant method to use (Moser & Stuart, 1953). To conclude, there is never going to be a complete dismissal of a particular sampling method. Quota sampling has no theoretical structure; however practicality outweighs its negatives. If a researcher is looking for, "results derived from theoretically safe sampling methods," then it is safe to say that quota sampling is out of the question (Moser & Stuart, 1953). If there are time and cost constraints to a researcher, then quota sampling can be convenient.

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