**Quota sampling** is a non-probability sampling method that uses the following steps to obtain a sample from a population:

**Step 1**: Divide a population into mutually exclusive groups based on some characteristic.

**Step 2:** Determine a proportion of each group to include in the sample.

**Step 3:** Survey individuals from each group that are convenient to reach.

The following example provides a scenario where quota sampling may be used in the real world.

**Example: Quota Sampling**

Suppose a tech company wants to know the opinion of customers about a new product. They decide to collect data from 1,000 customers from the following age groups in the corresponding proportions:

- Age 18 – 30: 40%
- Age 31 – 50: 40%
- Age 51-70: 20%

They can use the following steps to perform quota sampling:

**Step 1**: Divide the entire population of customers into three age brackets.

**Step 2:** Determine the number of individuals to include from each age group.

**Step 3:** Survey individuals from each group that are convenient to reach.

**Quota Sampling vs. Stratified Sampling**

Quota sampling and stratified sampling are similar because they both split a population into groups or *stratum*.

However, stratified sampling performs simple random sampling to select individuals to survey in each group while quota sampling uses convenience sampling to select individuals to survey in each group.

In technical terms, stratified sampling is a **probability sampling method** because each individual in the population has an equal chance of being included in the sample.

However, quota sampling is a **non-probability sampling method** because not every individual in the population has an equal chance of being included in the sample.

In this regard, stratified sampling has a higher likelihood of producing a representative sample but it tends to be more time-intensive and costly.

**Pros & Cons of Quota Sampling**

Quota sampling offers the following **pros**:

- It offers a more convenient way to gather data compared to other probability sampling methods since researchers can simply collect data on individuals that are convenient to reach.
- It offers a cheaper way to gather data compared to other probability sampling methods since researchers can spend less time and money on traveling to reach individuals.

However, quota sampling comes with the following **con**:

- It is not guaranteed to produce a representative sample since not every member of the population has an equal chance of being included in the sample. This means it may not be valid to generalize the findings from our sample to the overall population.

**When to Use Quota Sampling**

In practice, quota sampling is used most often when a research budget is limited or when data needs to be collected very quickly.

Since quota sampling allows researchers to survey individuals who are convenient to reach, only a minimal research budget is needed and data can often be gathered quickly using this method.

**Additional Resources**

Introduction to Sampling Methods

What is a Sampling Frame?

What is Sampling Variability?