Nonprobability sampling is a technique which is not based on the probability theory because elements are not randomly selected and it is a technique often used for qualitative research. When using nonprobability sampling, the individuals chosen meet a certain predetermined criteria or are selected due to their accessibility. Thus, not every individual in the population has an equal chance of being selected.
In nonprobability sampling, researchers tend to use their judgement when selecting subjects for observation. This technique does not mirror the principles held by simple random sampling (SRS) where personal decisions play no part. Thus, bias largely influences nonprobability sampling and can cause the results to be skewed.
Nonprobability sampling is utilized often because researchers are unable to achieve a random sample due to factors such as time and man power. The major disadvantage associated with nonprobability sampling is that the results collected cannot be used to draw assumptions or conclusions about the entire population. However, in some cases, nonprobability sampling is the only option. For example, if the population is essentially limitless, randomization may not be possible1. Additionally, if researchers want to prove that a particular characteristic exists within a population, then nonprobability sampling may be advantageous.
Nonprobability sampling is quite diverse in terms of the types of methods which can be used. Convenience sampling, judgemental sampling and snowball sampling are a few of these methods. Of these, convenience sampling is the most frequently employed and seeks to sample all subjects which are within an accessible range1. Even though nonprobability sampling has its limitations, it can be effective and thus, is relevant to the study of statistics.
References:
1. Explorable.com. (May 17, 2009). Non-Probability Sampling. Retrieved from: http://explorable.com/non-probability-sampling
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