Quota sampling is a non-probability sampling method that involves selecting individuals for a sample based on pre-defined quotas or proportions to ensure the sample represents specific characteristics or subgroups within a population. Quota sampling is commonly used when it is not feasible or practical to use probability sampling techniques, but there is a desire to achieve a certain level of representativeness in the sample.
Here are some key characteristics and considerations of quota sampling:
1. Defining quotas: Quota sampling requires the researcher to establish quotas or targets for different characteristics or subgroups in the population. These characteristics could be demographic variables such as age, gender, ethnicity, or other relevant variables based on the research objectives.
2. Non-random selection: Unlike probability sampling methods, quota sampling does not involve random selection of individuals. Instead, the researcher intentionally selects participants to fulfill the pre-defined quotas. The selection process may involve convenience or judgment sampling methods.
3. Proportional representation: Quota sampling aims to achieve proportional representation of the different characteristics or subgroups in the population. The researcher selects participants in a manner that ensures the sample reflects the desired distribution of the characteristics or subgroups based on the established quotas.
4. Researcher's judgment: The researcher uses their judgment to select participants who fit within the specific quotas. This introduces a subjective element into the sampling process, which can potentially introduce bias.
5. Lack of randomization: Since quota sampling does not involve random selection, the sample may not be representative of the entire population. The results obtained from a quota sample may have limitations in terms of generalizability.
Quota sampling is often used in market research, opinion polling, and surveys where the goal is to ensure representation of specific demographic groups or other relevant subgroups. It allows for efficient data collection by focusing on specific characteristics of interest while maintaining a degree of control over the sample composition.
However, it is important to note that quota sampling does not provide the same level of representativeness as probability sampling methods. Researchers should acknowledge the limitations and potential biases associated with quota sampling and interpret the findings accordingly, recognizing that the sample may not fully reflect the diversity and characteristics of the entire population.
