Non-Probability Sampling
Non-probability sampling is a sampling method in which participants are selected using non-random criteria, meaning not all members of the population have a known or equal chance of being included in the study.
On this page:
- What is Non-Probability Sampling?
- Types of Non-Probability Sampling
- Sample Size Considerations
- Advantages and Disadvantages
- When to Use Non-Probability Sampling
| Aspect | Non-Probability Sampling | Probability Sampling |
|---|---|---|
| Selection method | Non-random | Random |
| Chance of selection | Unknown | Known and non-zero |
| Bias level | Higher | Lower |
| Representativeness | Limited | High |
| Generalisation | Limited | Strong |
Probability vs Non-Probability Sampling at a Glance
Non-probability sampling prioritises practicality, whereas probability sampling prioritises representativeness.
Non-probability sampling means:
- Participants are selected based on availability or judgement
- Not everyone in the population has a chance to be selected
- Results are quick to obtain but less generalisable
It is mainly used for exploratory and qualitative research.
What is Non-Probability Sampling?
In non-probability sampling (also known as non-random sampling) not all members of the population have a chance to participate in the study. In other words, this method is based on non-random selection criteria. This is contrary to probability sampling, where each member of the population has a known, non-zero chance of being selected to participate in the study.
Necessity for non-probability sampling can be explained in a way that for some studies it is not feasible to draw a random probability-based sample of the population due to time and/or cost considerations. In these cases, sample group members have to be selected on the basis of accessibility or personal judgment of the researcher. Therefore, the majority of non-probability sampling techniques include an element of subjective judgement. Non-probability sampling is the most helpful for exploratory stages of studies such as a pilot survey.
Types of Non-Probability Sampling
The following is the list of the most popular non-probability sampling methods and their brief descriptions:
| Non-probability sampling method | Description |
| Judgement Sampling (Purposive Sampling) | Researcher chooses samples purely on the basis of her knowledge and credibility |
| Quota sampling | Researcher chooses sample group members on the basis of their shared traits or characteristics |
| Convenience sampling | Researcher chooses population members that are conveniently available to her. |
| Voluntary response sampling | Respondents voluntarily choose to participate in a study, usually through an online survey |
| Snowball sampling | Initially chosen sample group members help researcher to find new members |
| Consecutive sampling | Researcher selects a sample or group and after data collection and analysis moves to another sample |
Non-probability sampling methods
Sample Size Considerations
The issue of sample size in non-probability sampling is rather ambiguous and needs to reflect a wide range of research-specific factors in each case. Nevertheless, there are some considerations about the minimum sample sizes in non-probability sampling as illustrated in the table below:
| Nature of study | Minimum sample size |
| Semi-structured, in-depth interviews | 5 – 25 |
| Ethnographic | 35 – 36 |
| Grounded theory | 20 – 35 |
| Considering a homogeneous population | 4 – 12 |
| Considering a heterogeneous population | 12 – 30 |
Sizes of non-probability sampling[1]
In qualitative research, sample size is often determined by data saturation rather than fixed numbers.
Advantages and Disadvantages
The following are the main advantages of non-probability sampling methods:
- Possibility to reflect the descriptive comments about the sample
- Cost-effectiveness and time-effectiveness compared to probability sampling
- Effective when it is unfeasible or impractical to conduct probability sampling
Disadvantages include the following points:
- Unknown proportion of the entire population is not included in the sample group i.e. lack of representation of the entire population
- Lower level of generalization of research findings compared to probability sampling
- Difficulties in estimating sampling variability and identifying possible bias
When to Use Non-Probability Sampling
Non-probability sampling is most appropriate when practical constraints or research objectives make probability sampling unsuitable.
You should use non-probability sampling if:
- You are conducting exploratory or qualitative research
- A complete sampling frame is not available
- You are working under time or budget constraints
- You need to study specific or hard-to-reach groups
- Your aim is to generate insights rather than generalisable results
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[1] Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited