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Quota sampling does not allow random selection of participants of the research.Quota sampling helps in an easy comparison of two groups of research.Quota sampling can be used as a primary research method of researches of different types.
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Quota sampling is quite easy to conduct and administer as compare to the other similar research sampling methods.Select participants randomly who fulfill the criteria of research. The accuracy of research depends on the participants of the research group. In the next step, the researcher would select the participants of the research group. For example, if you are conducting a quota sampling on the 10,000 women, then you should at least choose 100-200 women in one sampling group. The next step is to select the size of the sample. For example, working women could be one in four in the particular city where research is being conducted. The next step in quota sampling is to establish the proportion of subgroups in quota sampling. The second group of women will include non-working women within the age group of 35-50. The first group of women will consist of working women within the age group of 35-50. In this way, two research groups can be formed. The first characteristics are to select women who belong to the age group of 35-50, and the second characteristic can be working or non-working women. For example, a researcher can create two groups of women based on two characteristics. Make sure that participants in the study belong to only one group. The first step in quota sampling is the creation of groups of individuals with similar characteristics or traits relevant to the research. The followings are the main three steps in creating a quota sample. The effectiveness of quota sampling can be ensured if the researcher has a clear understanding of the objective of research and in-depth knowledge about the population. The quota sampling method is more suitable for research types where the accuracy of the research outcome is not essential. For example, a researcher can interview people who coordinate with the interviewer as it is easy for him to obtain answers or researcher might include the people that are known to him to complete the number of participants of the research. There are more chances of biased outcomes in quota sampling. Because of this reason, stratified sampling is also known as the probability sampling method. The difference between these two methods is that in quota sampling, participants are not selected randomly from the population, whereas in stratified sampling, participants are chosen randomly from the population. The quota sampling method is quite similar to stratified sampling. Other factors can also be added to the subset as per the requirement of the research study. The selection of participants for research using the quota sampling method increases the effectiveness of the research and can be generalized for the entire population.įor example, two different groups of respondents from a population can be formed based on the gender of the respondents, and further participants can be selected based on their age or income factor. The population is then divided into subsets based on different aspects. The population for sampling is selected based on specific characteristics and traits of the members of the population. The quota sampling method is used in the initial stage of a research study. Quota sampling is also known as the non-probability sampling method. Quota sampling can be defined as a sampling method where a sample of respondents, with specific characteristics and traits, for research is selected from the population of interest.