Advantage of Stratified Sampling & Disadvantage of Stratified Sampling

       Advantage of Stratified Sampling:

1. Stratification tends to decrease the variances of the sample estimates. This results in smaller bound on the error of estimation. This is particularly true if measurements within strata are homogeneous.
2. By stratification, the cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.
3. When separate estimates for population parameters for each sub-population within an overall population are required, stratification is rewarding.
4. Stratification makes it possible to use different sampling designs in different strata.
5. Stratification is particularly more effective when there are extreme values in the population, which can be segregated into separate strata, thereby reducing the variability within strata.
6. Stratified sampling is most effective in handling heterogeneous population such as data on wages of industrial workers, amount of rain fall and the like.
7. Stratification provides a chance to improve sampling design considerably if the strata could be formed on the basis of natural characteristics.
8. In stratified sampling, confidence intervals may be constructed individually for the parameter of interest in each stratum. This is an added advantage over other methods of sampling.
9. The estimates in various strata may be made with whatever precision is desired simply by adjusting the sample size selected from each stratum.

        Disadvantage of Stratified Sampling:

The major disadvantage of stratified sampling is that it may take more time to select the sampling than would be the case for simple random sampling. More time sis involved because complete frames are necessary within each of the strata and each stratum must sampled.