Quota sampling

Definition

Quota sampling is a non-probability sampling technique where researchers ensure that specific characteristics of a population are represented in the sample, according to predetermined quotas. This method involves segmenting the population into subgroups and selecting samples from these groups until the quota for each is met, which allows researchers to control for certain variables without using random selection.

5 Must Know Facts For Your Next Test

1. Quota sampling is often used when researchers want to ensure that specific demographic groups are represented, such as age, gender, or income levels.
2. This method does not involve random selection, which can lead to sampling bias if the quotas are not carefully defined and followed.
3. Quota sampling can be quicker and more cost-effective than probability sampling methods, making it appealing for market research and opinion polling.
4. Researchers may set quotas based on previous research or estimates about the population's characteristics to guide their sampling process.
5. While quota sampling allows for representation of certain groups, it may compromise the generalizability of findings due to the non-random nature of sample selection.

Review Questions

• How does quota sampling differ from stratified sampling in terms of selection methodology?
  • Quota sampling differs from stratified sampling primarily in its selection methodology. In quota sampling, researchers set predetermined quotas for specific characteristics and select participants non-randomly until those quotas are filled. In contrast, stratified sampling involves dividing the population into subgroups and randomly selecting samples from each subgroup, ensuring that each subgroup is proportionately represented. This fundamental difference impacts the potential for bias and the overall validity of the results.
• Discuss the potential advantages and disadvantages of using quota sampling compared to other sampling methods.
  • Using quota sampling can provide several advantages such as cost-effectiveness and speed, particularly when time is limited or resources are constrained. It allows researchers to focus on specific demographic segments that are essential for their study. However, the disadvantages include an increased risk of sampling bias since participants are not chosen randomly, which can affect the reliability and generalizability of the findings. Other methods like random sampling may yield more accurate results but require more time and resources.
• Evaluate how quota sampling might impact the overall findings of a study if not executed carefully.
  • If quota sampling is not executed carefully, it can significantly impact the overall findings of a study by introducing systematic biases. For instance, if researchers fail to accurately define quotas or select participants based solely on convenience rather than representative criteria, this may lead to overrepresentation or underrepresentation of certain groups. Consequently, the results might misrepresent the population's views or behaviors, undermining the study's validity and making it difficult to draw accurate conclusions applicable to the larger population.

Related terms

Stratified sampling: A probability sampling method where the population is divided into subgroups (strata) based on shared characteristics, and samples are randomly selected from each stratum.

Non-probability sampling: A sampling technique where not all members of the population have a chance of being included in the sample, often leading to biases.

Sampling bias: A systematic error that occurs when certain individuals or groups in a population are more or less likely to be included in the sample, which can distort research findings.