In probability, each unit of the population has a known (non-zero) probability of being included in the sample, and samples are selected randomly by using some random selection method. That’s why probability sampling may also be called random sampling. In probability sampling, the reliability of the estimates can be determined. In probability sampling, samples are selected without any interest. The advantage of probability sampling is that it provides a valid estimate of sampling error. Probability sampling is widely used in various areas such as industry, agriculture, business sciences, etc.
Important types of probability sampling are
- Simple Random Sampling
- Stratified Random Sampling
- Systematic Sampling
- Cluster Sampling
In this sampling technique samples are selected by personal judgment due to this personal judgment in the selection of sample bias may include which makes the result unrepresentative. This sampling technique may also be called non-random sampling. The disadvantage of non-probability is that the reliability of the estimates cannot be determined.
The Non-Probability Samplings are:
- Purposive sampling
- Quota sampling
- Judgment sampling
- Snowball sampling
- Convenience sampling
Differences between Probability and Non-Probability Sampling
The difference between these two is that non-probability sampling does not involve random selection of objects while in probability sampling objects are selected by using some random selection method. In other words, it means that non-probability samples aren’t representative of the population, but it is not necessary. However, it may mean that non-probability samples cannot depend upon the rationale of probability theory.
In general, researchers may prefer probabilistic or random sampling methods over a non-probabilistic sampling method, and consider them to be more accurate and rigorous. However, in applied social sciences, for researchers, there may be circumstances where it is not possible to obtain sampling using some probability sampling methods. Even practical or theoretical it may not be sensible to do random sampling. Therefore a wide range of non-probability sampling methods may be considered, in these circumstances.
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