Non-Probability Sampling Technique

Non-probability technique is one of the sampling technique which helps researcher to create sample from a population of interest (target population) for a particular study.


In non-probability sampling technique, the participants do not get equal chances of being selected. This technique is based on the subjective judgement of the researcher, rather than random selection (i.e., probabilistic methods) unlike probability sampling techniques.


The main difference between probability sampling and non-probability sampling is that former uses some form of random selection but the later does not use any type of random selection for sampling purpose.


Although, non-probability samples may or may not be true representative of the population and are less desirable than probability samples, sometimes it becomes difficult for researcher to get probable samples or researcher is least interested in generalizing the result to a larger population. In that scenario, non-probable sample can be considered for the study.


Advantages of Non-probability sampling

  • Cost-effective and time-effective (compared to probability sampling)

  • Easy to use

  • Helpful when probability sampling cannot be used

Disadvantages of Non-probability sampling

  • Unknown how well the population is represented through selected sample

  • Results/outcomes generalization in larger population is difficult

  • Calculation of confidence intervals and margins of error is impossible

Types of non-probability sampling technique


1. Convenience Sampling


Convenience sampling has been considered to be the most commonly used technique. It is one of the easiest, less-expensive and time-saving technique which works on the basis of convenience of the researcher. In this technique, researcher selects samples who all are easily accessible/reachable to the researcher.

This technique can introduce bias during sampling. Sample created by this technique may not represent the larger population. Convenience technique is also known as accidental sampling, opportunity sampling or grab sampling. It is often used during preliminary research effort to get an estimate without much investment on time and cost to select sample.


Advantages of Convenience sampling

  • Useful for pilot studies

  • Cost effective and less time consuming

  • Simple and easy to use

Disadvantages of Convenience sampling

  • Highly vulnerable to selection bias

  • High level of sampling error

  • Results are not generalizable


2. Purposive Sampling

Purposive sampling is also known as judgmental sampling.


In this technique, researcher selects sample on the basis of his/her prior experience or belief that certain candidates will be suitable for the particular study. Researchers would like to go with their judgment regarding selection of sample.


For example, survey is planned for knowledge about childcare in early childhood. Researcher plans to select new mothers over first time pregnant women thinking that new mothers would definitely provide sound results.

This kind of technique can introduce personal biasness. But, if this technique is applied properly, good results can be expected at the end. This technique uses personal judgment to choose suitable samples which can help to answer research questions appropriately.


Advantages of Purposive sampling

  • Allow researcher to hand pick

  • Researcher’s experience can be used for sample selection

Disadvantages of Purposive Sampling

  • May introduce selection bias

  • Limited generalizability

3.Snowball Sampling

Snowball sampling is also known as network sampling or chain-referral sampling.


This technique is used when features need to be studied are rare and difficult to find. In this technique, samples are created through chain referrals. Subjects refer the researcher to others who might be recruited as subjects.


For example – researcher wants to study the experiences of individuals who spent long time in the jail. Researcher may not get enough sample in such cases but if researcher manages to get one candidate for study. That candidate can further refer other suitable individuals for the study.


This technique is useful when study participants are difficult to identify, locate or access. One or more identified sample can recommend others for the study.


Advantages of Snowball sampling

  • Enable access to difficult population

  • Useful for studying specific cases

  • Cost effective

  • Less resource required

Disadvantages of snowball sampling

  • Limited generalizability

  • May introduce bias

  • Representativeness of the sample is not guaranteed

  • Less control over the sampling method


4. Quota Sampling

This method aims to reflect that certain number of study participants from different subgroups are taken to create sample so that selected sample represent certain characteristics of the population. In this technique, population is classified into different sub-groups on the basis of different criteria such as age, gender, education, etc.


The base of quota sample is that sample groups being studied are proportional to the groups in the population.


For example – researcher wants to study pizza lover males and females in a society where 2500 individuals (1500 males and 1000 females) are staying. He first identifies the sub-groups (strata) of male and female. Then researcher chooses the sample units by judgement or convenience from each group based on specified proportion.


The main difference between quota sampling and stratified sampling is that quota sampling uses non-random methods to create sample unlike stratified sampling until the pre-fixed quota by researcher is fulfilled.


Advantages of Quota sampling

  • Includes specific subgroups in the proportion desired

  • Useful for examining group differences

Disadvantages of Quota sampling

  • Can not set quota for all characteristics which may be important to study

  • May introduce selection bias