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Various methods of data collection in the form of sampling are used in statistical research in order lower the cost, be time efficient and at the same time, produce reliable results. Both probability and non-probability sampling have been carried out in data collection for research purposes but there has been much discussion on which method is more acceptable and produces reliable results. Quota sampling, a form of non-probability sampling, is used in ‘commercial’ research where the advantage of being a quick, time and cost efficient method is appreciated. However, random sampling is generally preferred in statistical research where low bias and high precision yields reliable results.
What are Quota and Random Sampling?
Quota sampling is defined as ‘a non-probability technique where the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics’ (Experiment Resources, 2010). Quota sampling is carried out by dividing the population into subgroups and calculating their proportions in relation to the population. The subjects are selected from the various subgroups. The subjective selection of samples is what differs from other random sampling methods. This involves a ‘pre-determined’ choice on behalf of the person carrying out the data collection and they can choose the sampling units by any means necessary unless specific instructions are given.
Random sampling is a form of probability sampling where every possible sample unit has an equal chance of being chosen. This could be done by assigning a number to every sampling unit and using a computer generated random number table to select them. Stratified random sampling follows the same procedure as quota sampling except for the last step. Instead of giving the person carrying out the sampling method discretion to pick whoever fits the quota, the sample is picked randomly.
Comparison of Quota and Random Sampling