Probability sampling provides a scientific technique of drawing samples from the population according to some laws of chance in which each unit in the universe has some definite pre-assigned probability of being selected in the sample. There are different types of sampling where:
- Each sample unit has an equal chance of being selected.
- Sampling units have different probabilities of being selected.
- The probability of selection of a unit is proportional to the sample size.
Some basic types of probability sampling methods are:
- Simple Random Sampling.
- Stratified Random Sampling.
- Cluster Sampling.
- Systematic Sampling.
- Multi-stage Sampling.
We now list out some of the advantages and disadvantages of probability sampling methods:
Advantages of Probability Sampling:
- There is no bias due to the personal biases of the researcher and the sample is representative of the population.
- We can calculate the standard error/variance which allows us to obtain confidence intervals for the parameter.
- The probability sampling methods can be optimized to save time and money while minimizing the total error.
- The probability sampling methods are much easier to carry out since there is a mechanical procedure to follow. On the other hand, non-probability judgemental sampling methods require the investigator to think carefully before trying to include a particular unit in the sample.
Disadvantages of Probability Sampling:
- If the sample size is too small then the sample may not be representative of the entire population and this may lead to incorrect conclusions.
- In any probability sampling method, the sampling error cannot be entirely eliminated. Only complete enumeration can give 100% certainty.
- Probability sampling works well only if the complete and up-to-date frame is available and if the units are randomly arranged. However, these requirements are not generally fulfilled.
References:
Business Statistics – SC Gupta and Indra Gupta
