# Quota Sampling: Definition, Method & Examples

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• 0:01 Sampling Methods
• 0:53 What Is Quota Sampling?
• 2:07 Quota Sampling Method
• 6:16 Lesson Summary

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Lesson Transcript
Instructor: Gloria Kray
Market researchers and political pollsters often use a non-probability sampling approach to quickly and easily gather data while minimizing costs in time and money. In this lesson, quota sampling will be defined and examples provided.

## Sampling Methods

In the research process, once the researcher decides who to study, he then needs to select a sample from the target population. To do this, the researcher selects from two basic sampling methods: probability and non-probability. In probability sampling, each element of the population has a known chance of being selected. A common probability sampling method is random sampling, where each element has an equal chance of being selected. In non-probability sampling, the selection of elements is based in some part on the judgment of the researchers. The selection relies on the personal judgment of the researcher rather than on chance to select the sample elements. Common types of non-probability sampling are convenience, judgment, and quota sampling.

## What Is Quota Sampling?

Quota sampling is a type of non-probability sampling that involves a two-step process:

Step 1: Specify a list of relevant control categories or quotas such as age, gender, income, or education. A quota is some specific requirement or predefined category. The target population is first segmented into mutually exclusive sub-groups, which means that one individual can be a member of only one category or sub-group. The researcher takes special care to obtain a sample that is similar to the target population on some specified control category.

Step 2: Collect a sample that has the same properties as the target population. To do this, the researcher must know the distribution of these properties across that population. For example, let's look at a target population of college students at a local college. Because the researcher can access this data, he knows that in this given population, 43% of the students are male and 57% are female. For a sample size of 1,000, the researcher knows that 430 males and 570 females will need to be interviewed from that population.

## Quota Sampling Method

To more realistically represent a given population, it would be necessary to control more than one category. For example, the researcher could select gender and age, or gender and income, or level of education and income, depending on the purpose of the study. Using our example, the researcher could add age (less than 21 years and 21 years and over) as a control category, specifying that half of the sample for each gender be from each age category. Now we are searching for 215 males under 21 years and 215 males 21 years and over, along with 285 females under 21 years and 285 females 21 years and over. What has happened here is that with every added category, it may take longer to locate these individuals, thus adding cost and time to the process. However, the target population could be better represented if additional categories are considered.

Why use multiple quotas? The intent of specifying multiple control categories or quotas is to improve the representation of particular groups within the population and ensure that groups are not over-represented. In our example, males and females would be interviewed until each category has reached its quota. Once 215 males under 21 years of age have been interviewed, no further male responses from that age category will be considered. Individuals for the remaining categories will continue to be interviewed until each quota is satisfied. This ensures that no more than 215 males and 285 females from each age category will be represented. In this way, no one category is over-represented according to the target population.

Let's consider some distinct advantages of quota sampling.

1. It is a useful technique to use in the preliminary stages of research.
3. It allows the researcher to easily compare groups.
4. It is useful when detailed accuracy is not important.
5. It can be used to obtain representative samples at a relatively low cost.
6. It may sometimes be the only approach that can be used.
7. Under certain conditions, it can obtain results close to those for conventional probability sampling. It is widely used by market researchers and political pollsters.

While there are many advantages of quota sampling, it's important to also look at the disadvantages of this method as well.

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