The term probability sampling is used when the selection of the sample is purely based on chance. The human mind has no control over the selection or non-selection of the units for the sample. Every unit of the population has a known nonzero probability of being selected for the sample. The probability of selection may be equal or unequal but it should be non-zero and should be known. Probability sampling is also called random sampling.
Some examples of random sampling are:
- Simple random sampling
- Stratified random sampling
- Systematic random sampling
In non-probability sampling,the sample is not based on chance. Rather, it is determined by a person. We cannot assign the probability of an element of the population being selected in the sample. Somebody may use their personal judgment in the selection of the sample. In this case the sampling is called judgment sampling. A drawback of non-probability sampling is that such a sample cannot be used to determine the error. Any statistical method cannot be used to draw inference from this sample. However, judgment sampling becomes essential in some situations. Suppose we have to take a small sample from a big heap of coal. We cannot make a list of all the pieces of coal. The upper part of the heap might have big pieces of coal, and we have to use our judgment in selecting a sample to have an idea about the quality of the coal. Non-probability sampling is also called non-random sampling.