Simple Random Sampling:
Simple random sampling is a method of selecting “n” elements from a population of size “N” elements in such a way that each combination of “n” elements has an equal probability of being selected as every other combination.
Advantages:
- This method provides the foundation for much statistical theory.
- This provides a basis for which other methods can be compared.
- Each sampling unit has the same probability of being selected, so there is no need to weight the observation in computation.
- There is no constraint on the observation of the relative location and sequence of the observations.
Disadvantages:
- Sampled individuals may be so widely dispersed.
- Assuming one homogenous population, specific subgroups may be overlooked or overrepresented due to chance factors.
- When the population measurements are considerably large, simple random samples produce more significant variances than the other sampling methods.
- If so, this design is inefficient, with too many samples to achieve the desired precision.
