Explain Quota Sampling.
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Quota sampling is a non-probability sampling technique used in research to ensure that the final sample represents certain characteristics or quotas of the population. Unlike random sampling methods, quota sampling involves the intentional selection of participants based on specific criteria, often predetermined by the researcher. Here's how it works:
Identification of Quotas: Researchers identify specific characteristics or traits (e.g., age, gender, socioeconomic status) deemed important for representation in the sample.
Division of Population: The population is divided into different strata based on the identified characteristics, and quotas are set for each stratum.
Non-Random Selection: Participants are then selected non-randomly, with the aim of filling the quotas set for each stratum. This can be done through various methods, such as convenience sampling or judgment sampling.
Data Collection: Data is collected from individuals who fit the predetermined quotas, ensuring a proportional representation of the characteristics of interest in the final sample.
Quota sampling is often more feasible and cost-effective than some probability sampling methods, but it may introduce biases if not carefully implemented. Researchers need to be mindful of potential limitations and ensure that the selected quotas accurately reflect the diversity within the population under study.