Non-Probability Sampling

In non-probability sampling (also known as non-random sampling) not all members of the population has a chance of participating in the study. 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

Minimum non-probability sample size[1]

The following is the list of the most popular non-probability sampling methods:

  1. Judgement Sampling
  2. Quota Sampling
  3. Convenience Sampling
  4. Extensive Sampling

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