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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:

1. Each sample unit has an equal chance of being selected.
2. Sampling units have different probabilities of being selected.
3. The probability of selection of a unit is proportional to the sample size.

Some basic types of probability sampling methods are:

1. Simple Random Sampling.
2. Stratified Random Sampling.
3. Cluster Sampling.
4. Systematic Sampling.
5. Multi-stage Sampling.

We now list out some of the advantages and disadvantages of probability sampling methods:

1. There is no bias due to the personal biases of the researcher and the sample is representative of the population.
2. We can calculate the standard error/variance which allows us to obtain confidence intervals for the parameter.
3. The probability sampling methods can be optimized to save time and money while minimizing the total error.
4. 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.

1. 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.
2. In any probability sampling method, the sampling error cannot be entirely eliminated. Only complete enumeration can give 100% certainty.
3. 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

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