Purposive Sampling | Definition & Examples

Purposive sampling—also known as judgment sampling—is a non-probability sampling technique. The researcher intentionally selects individuals to study because they possess specific traits or characteristics. In other words, the sample is chosen “on purpose” instead of randomly.

Though purposive sampling can be more convenient and less expensive than other sampling methods, it is heavily susceptible to sampling bias. Purposive sampling is common in qualitative research, particularly in fields like marketing, medical research, and other sciences.

What is purposive sampling?

Purposive sampling is a sampling method where the researcher handpicks individuals to include in their study based on certain characteristics or experiences. It is a form of non-probability sampling, as not every individual in the population has an equal chance of being included.

Purposive sampling can be a helpful sampling technique if the researcher has a strong understanding of the population they want to study, as it allows them to select the individuals they believe best represent this group. However, because the researcher’s preconceptions are directly reflected in the sample they select, purposive sampling is very vulnerable to sampling bias and may not generalize (i.e., it lacks external validity).

Purposive sampling techniques and examples

Purposive sampling encompasses a range of non-probability sampling techniques, each with a distinct purpose. The following sections describe several common types.

Maximum variation sampling

Maximum variation sampling (also known as heterogeneous sampling) involves selecting individuals who differ from one another as much as possible, including typical and more extreme cases.

The purpose of maximum variation sampling is to capture the widest possible range of perspectives and identify common themes across diverse individuals.

Homogeneous sampling

Homogeneous sampling is the opposite of maximum variation sampling. Rather than focusing on people who are very different from each other, it involves selecting individuals who share specific traits or experiences.

Homogenous sampling helps describe a specific subgroup from the population and their experiences in detail. This technique is often used to select focus group participants.

Typical case sampling

Typical case sampling focuses on individuals who best reflect the average or most common characteristics of the population.

The purpose of typical case sampling is to describe a topic of interest using representative cases. The goal is to gain contextual insight rather than obtain results that statistically generalize to the broader population.

Extreme case sampling

Extreme case sampling, or deviant case sampling, is used to study unusual cases or outliers. These cases might include individuals who are unusually above or below average in some domain.

These unusual examples can be used as a cautionary tale or provide insight that would be less apparent from general cases.

Critical case sampling

Critical case sampling involves selecting cases that are particularly important or broadly informative. Cases are considered critical if their patterns are likely to hold in similar situations (i.e., “if it happens here, it will happen anywhere”).

Though the findings from critical case sampling can be applied to similar cases, the results cannot be used to make statistical inferences. Critical case sampling can therefore be helpful during earlier, more exploratory research.

Expert sampling

Expert sampling involves selecting people with specialized knowledge or expertise in a certain area.

Talking to experts, who might not be included when using probability sampling techniques, can be helpful for exploratory research.

Pros and cons of purposive sampling

Any research method or sampling technique has pros and cons that need to be considered. When deciding whether to use purposive sampling, you should consider its advantages and disadvantages.

Advantages of purposive sampling

Purposive sampling has several benefits.

• Good for exploratory research: Due to its flexibility, purposive sampling is often helpful when studying a new topic about which little is known.
• Access to hard-to-reach populations: Purposive sampling allows the research to study individuals who may be missed by random sampling (e.g., experts, people with unique experiences).
• Convenience: Researchers can select individuals to study who are both easily accessible and best suited to their research questions.
• Efficiency: Purposive sampling allows researchers to select the most relevant individuals, resulting in rich and useful data and reducing research time and costs.

Disadvantages of purposive sampling

There are also several drawbacks to purposive sampling.

• Susceptible to bias: Because the researcher hand-picks participants, their own biases may be reflected in the sample.
• Limited generalizability: Because a purposive sample is not randomly selected or representative, findings cannot be used to make statistical inferences about the broader population.
• Risk of overlooking alternative perspectives: The researcher may inadvertently exclude groups they are not aware of.

Frequently asked questions about purposive sampling

What is an example of purposive sampling?

Purposive sampling, or judgment sampling, is a non-probability sampling method that involves hand-picking individuals to include in a study based on certain characteristics.

For example, a researcher studying how cancer patients cope with terminal illness may directly recruit several late-stage cancer patients who are receiving palliative care at their clinic.

Unlike in probability sampling, not every cancer patient has an equal chance of being selected. Instead, the researcher can choose the cases they feel will be most informative.

Purposive sampling can be helpful when the researcher is very familiar with the population they are studying, as it allows them to select individuals who best represent this group. However, any biases the researcher holds may be reflected in the sample.

What is the difference between purposive sampling and convenience sampling?

Purposive sampling and convenience sampling are two non-probability sampling methods, meaning not every individual from the population has an equal chance of being selected. Sampling methods are ways of choosing individuals from a population to study.

Purposive sampling is when a researcher hand-picks individuals because they possess specific traits or characteristics. For example, someone studying successful teaching techniques might only include teachers who have recently won awards in their sample.

On the other hand, convenience sampling involves selecting individuals simply because they are easily accessible. For example, a business might ask their social media followers to complete a survey.

Convenience sampling and purposive sampling are not mutually exclusive—a researcher might use some combination of both techniques when obtaining a sample for their study.

Both of these techniques are susceptible to sampling bias. Individuals who are readily accessible or who the researcher chooses to participate may not be fully representative of the broader population.

What is the difference between random sampling and purposive sampling?

Random sampling—or probability sampling—includes a range of sampling methods used to select a subgroup of individuals from a larger population. A key characteristic of random sampling is that every individual has a known chance of being selected.

Purposive sampling, on the other hand, is a non-probability sampling technique. In this method, not every individual has a known chance of being included in the sample. Instead, the researcher chooses who they include in their sample based on certain traits or experiences. This can be helpful if the researcher is very familiar with the population they are studying and wants to gain rich, targeted insight rather than generalizable information.

Purposive sampling is often easier and more efficient than random sampling. However, purposive sampling is highly susceptible to sampling bias. Random sampling is a better approach for obtaining a representative sample that reflects the broader population.

What is sampling bias?

Sampling bias occurs when some individuals in the population are more likely to be included in a sample than others. This can limit how well results generalize to the broader population.

Sampling methods like probability sampling help reduce sampling bias because every individual in the population has a known, non-zero chance of being included in the sample. However, it’s difficult to eliminate sampling bias entirely, so results from a sample should always be interpreted with caution.

What are the types of purposive sampling?

Purposive sampling is a sampling method where the researcher intentionally selects individuals to study based on desired characteristics or experiences relevant to their research question.
There are several common approaches to purposive sampling:

• Maximum variation (heterogeneous) sampling: includes individuals who differ from each other as much as possible to capture a range of experiences
• Homogeneous sampling: includes individuals who are very similar to each other to enable a detailed exploration of a certain subgroup
• Typical case sampling: includes individuals who best reflect the average or norm of a population
• Extreme (deviant) case sampling: includes outliers who fall significantly above or below the norm
• Critical case sampling: includes individuals whose results are likely to generalize—if it happens to them, it would probably happen to anyone

Expert sampling: includes individuals with specialized knowledge or expertise relevant to the research topic