# Quota Sample (Statistics)

## What is Quota Sampling?

Quota sampling is a non-probability sampling technique wherein the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits or focused phenomenon. It is a method of stratified sampling in which the selection of the sample is made by the interviewer, who has been given quotas to fill from specified subgroups of the population.

## Understanding Quota Sampling

Quota sampling involves the division of the population into exclusive subgroups, such as age, sex, ethnicity, income, or education level. The researcher then determines the proportions of these subgroups in the target population either through prior knowledge or research. Once the proportions are established, the researcher sets quotas for each subgroup to ensure that the sample reflects those proportions.

For example, if the population consists of 50% females and 50% males, a researcher with a sample quota of 100 individuals would aim to select 50 females and 50 males. The actual selection within these categories is non-random, often based on convenience or judgment of the researcher, which is why quota sampling is not considered a probabilistic sampling method.

• Cost-Effective: Quota sampling can be less expensive and quicker to implement than probability sampling methods.
• Convenience: It allows researchers to sample a population that is conveniently available, which is useful when working under time constraints or with limited resources.
• Control: Researchers can ensure that specific subgroups of the population are represented in the sample to a degree that reflects their presence in the target population.
• Flexibility: Quota sampling can be adapted for most types of research and can be used when a list of the population is not available.

• Subjectivity: The non-random selection of participants can introduce bias, as the researcher may subconsciously select individuals who fit certain criteria or are easily accessible.
• Lack of Representativeness: Since the selection is not random, the sample may not be representative of the population, limiting the generalizability of the results.
• Sampling Error:

It is difficult to estimate the sampling error or the degree to which the sample deviates from the population parameters.

• Over- or Under-representation: Some subgroups may be over- or under-represented if the quotas are based on inaccurate or outdated information about the population.

## Quota Sampling in Practice

Quota sampling is commonly used in market research and opinion polling. For instance, a company may want to understand the preferences of its customer base regarding a new product. The company can use quota sampling to ensure that the sample reflects the diversity of its customers in terms of age, gender, or other relevant factors.

Another common application is in exit polling during elections. Pollsters use quota sampling to quickly and efficiently gather information about voters' behaviors and attitudes while ensuring that the sample reflects the demographic makeup of the electorate.

## Conclusion

Quota sampling is a practical and efficient sampling method that can provide valuable insights, especially when time and resources are limited. However, due to its non-random nature, it is prone to bias and may not always produce results that are generalizable to the entire population. Researchers must carefully consider these limitations when choosing to use quota sampling and when interpreting the results obtained from such samples.

Despite its drawbacks, quota sampling remains a popular choice for researchers in various fields due to its simplicity and cost-effectiveness. When used appropriately and with a clear understanding of its limitations, quota sampling can be a powerful tool in the researcher's toolkit.