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.

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]


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


Advantages of Non-Probability Sampling

  1. Possibility to reflect the descriptive comments about the sample
  2. Cost-effectiveness and time-effectiveness compared to probability sampling
  3. Effective when it is unfeasible or impractical to conduct probability sampling


Disadvantages of Non-Probability Sampling

  1. Unknown proportion of the entire population is not included in the sample group i.e. lack of representation of the entire population
  2. Lower level of generalization of research findings compared to probability sampling
  3. Difficulties in estimating sampling variability and identifying possible bias


My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach contains a detailed, yet simple explanation of sampling methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in this e-book in simple words.

John Dudovskiy


Non-Probability Sampling


[1] Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited