What are the differences between proportionate and disproportionate stratified sampling?
The Correct Answer and Explanation is:
Correct Answer:
The key difference between proportionate and disproportionate stratified sampling lies in how samples are allocated to different strata based on their size in the population. In proportionate stratified sampling, the sample size from each stratum is proportional to the stratum’s size in the population. In disproportionate stratified sampling, the sample size from each stratum is not proportional to its size in the population.
Explanation
Stratified sampling is a method of sampling that involves dividing a population into distinct subgroups or “strata” based on specific characteristics such as age, income, education, or location. After stratifying the population, samples are drawn from each group to ensure representation across the different segments. This approach improves the accuracy and representativeness of results, especially when population subgroups differ significantly.
Proportionate stratified sampling ensures that the number of samples taken from each stratum corresponds to the stratum’s share of the overall population. For example, if 60% of a population belongs to Stratum A and 40% to Stratum B, then 60% of the total sample would be taken from A and 40% from B. This method provides an accurate reflection of the population structure and reduces sampling bias.
Disproportionate stratified sampling, on the other hand, does not follow the exact proportions of the population strata. Instead, researchers might deliberately oversample or undersample certain strata. This is often done when some strata are too small to yield meaningful analysis in a proportionate sample or when certain groups are of particular interest. For instance, if Stratum B is a minority group of analytical importance, a larger sample may be drawn from it, despite its small size in the population.
While proportionate sampling provides better population estimates, disproportionate sampling is useful for detailed subgroup analysis. However, disproportionate samples typically require statistical weighting to make the results generalizable to the overall population.
In summary, the choice between proportionate and disproportionate stratified sampling depends on the research objectives—accuracy in population representation versus deeper insight into specific subgroups.
