This is a key question for this method. We must consider the goal of using quotas: making the sample as representative as possible of the population being studied. From this point of view, we should choose to define quotas with variables that meet two conditions : 1 they can be altered, with respect to the population, by the nonrandom selection process that we use, and 2 they can have the greatest effect on the data that we want to measure.
Suppose that we want to measure the percent of a population that smokes by sampling from an online panel. What variables should we choose to define our quotas? We can do away with regional quotas. Rather, they recruit participants through online media, which can be accessed from any region. As for the second criterion quotas that could affect the result measured , we could opt to add a gender quota : smoking habits are different for men and women.
We are still unable to calculate the margin of error and the confidence level of the results. In other words, using quotas does not enable us to measure the precision of our results. Does that mean that there's no difference between using and not using quotas? That availability sampling is just as good as quota sampling? Definitely not! Using quotas gives us a certain degree of control over biases that may arise from the selection method used; it ensures that in a key series of variables, the composition of the population will be faithfully mirrored in our sample.
The problem is that we cannot state just how representative our sample is—even though this is common practice for many researchers. Despite all that, quota sampling is among the most popular sampling methods, and is practically the only viable method when conducting online research unless we have a random panel. Quotas are an effective and affordable system for obtaining samples that provide relevant information.
The biggest advantage of quota sampling is that it offers usable results at an affordable cost and, if the variables for segmentation have been chosen properly, those results tend to be reliable. There are two main disadvantages: 1 It is impossible to delimit any error we may be committing when using this sampling method and 2 there is the risk that some relevant quota could be left out of the study.
Advantages of Quota Sampling 1. Quota sampling emerges as an attractive choice when you are pressed for time, because primary data collection can be done in shorter time.
Quota sampling is not dependent on the presence of the sampling frames. In occasions where suitable sampling frame is absent, quota sampling may be the only appropriate choice available. Disadvantages of Quota Sampling 1. Same as other non-probability samplingmethods, in quota sampling it is not possible to calculate the sampling error and the projection of the research findings to the total population is risky.
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Adaptive cluster. Smith T. On the validity of inference from non random samples. Journal of the royal statistics society. Strauss A, Cobin J. Basic of qualitative research grounded theory, procedures and techniques. Stephen F, McCarthy P. Rejected Articles 2 7. Location: 50 responses per state Depending on the type of research, the researcher can apply quotas based on the sampling frame. Select your respondents How to perform quota sampling: Probability sampling techniques involve a significant amount of rules that the researcher needs to follow to form samples.
Here are the steps: Divide the sample population into subgroups: With stratified sampling, the researcher bifurcates the entire population into mutually exhaustive subgroups, i. Here, the researcher applies random selection. Figure out the weightage of subgroups: The researcher evaluates the proportion in which the subgroups exist in the population.
Select an appropriate sample size: In the third step, the researcher should select the sample size while maintaining the proportion evaluated in the previous step. If the population size is , the researcher can pick a sample of 50 elements. The sample chosen after following the first three steps should represent the target population. Conduct surveys according to the quotas defined: Make sure to stick to the predefined quotas to achieve actual actionable results.
Characteristics of quota sampling: Here are the top ten characteristics of quota sampling Aims to get the best representation of respondents in the final sample. Quotas replicate the population of interest in a real sense. The estimates produced are more representative. The quality of quota samples vary. Saves research data collection time as the sample represents the population.
Saves research costs if the quotas accurately represent the population. It monitors the number of types of individuals who take the survey. The researcher always divides the population into subgroups. The sample represents the entire population. Researchers use the sampling method to identify the traits of a specific group of people. Advantages of quota sampling Here are the top four advantages of quota sampling Saves time: Because of the involvement of a quota for sample creation, this sampling process is quick and straightforward.
Research convenience: By using quota sampling and appropriate research questions, interpreting information and responses to the survey is a much convenient process for a researcher.
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