![]() ![]() Firstly, using quota sampling ultimately limits the statistical inferences that can be made with the data. There are many disadvantages that are associated with quota sampling. ![]() This is something random sampling doesn’t guarantee Quota sampling allows the researcher to adjust into its sample groups of interest in the proportion they occur in the population, making the comparison of the sample to the population more certain. For example, a random sampling method is not likely to produce a sample which represents all ethnicity groups in the proportion they exist in the population. the reaction of the general public to a particular event.Īnother advantage of quota sampling over random sampling is that it allows the researcher to have control over the sample. This can be very practical in the real world, if data needs to be obtained very quickly i.e. Quota sampling methods allow a sample to be carried out within a very short space of time, compared to random sampling. Not only this, there is no need for calling back any non-respondents, so administrative costs of the quota sampling method are reduced significantly (Moser & Stuart, 1953). In other words, quota sampling is independent of any sampling frames. In random sampling methods, all the population needs to be listed first before you can use a random number generator to select your sample this process is completely eliminated when using the quota sampling method. if you have to sample 50 women, then you just need to sample the first 50 women you find, regardless of where they live, saving lots of time and money on travelling (Moser & Stuart, 1953). Travel costs are much cheaper, as your objective is to satisfy your quota, of course this would be constrained by the control, i.e. The biggest case for it is that is incredibly cheap to carry out. For a random sample to be carried out, there also needs to be a sampling frame.Īlthough quota sampling is criticised heavily by academics, it does have its advantages. Random sampling is defined as when every unit in the population has a probability of being chosen. The number of sampling units chosen from each stratum is based on proportion. However, the difference is, in quota sampling, judgement is used instead of randomness to select units from each stratum. Quota sampling involves stratifying a population into mutually exclusive sub-groups, as if using the stratified sampling method. Since we are looking at specifically quota sampling, we need to define it. 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. Examples of probability methods are stratifying sampling, cluster sampling, systematic sampling and simple random sampling. Quota sampling is a non-probability sampling method, compared to random sampling methods, which are known as probability sampling methods. ![]()
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