Advantages of stratified random sampling

Stratified random sampling is a way of sampling that involves the division of a population into smaller groups based on common characteristics. Stratified random sampling has several advantages over other types of sampling, such as increased accuracy, increased precision, and increased efficiency. • Increased Accuracy: By separating the population into homogeneous groups, more accurate and representative samples can be identified. Stratified random samples can ensure that all important subgroups of a population are accounted for and given an appropriate representation when selecting random samples. • Increased Precision: With a stratified random sample there is a reduced chance of sampling bias occurring. When using this technique, the sample size should not have an influence on the results. Using a stratified random sample also mitigates the risk of a survey designer omitting important variables. • Increased Efficiency: Stratified random sampling can reduce the total sample size required compared to other types of random sampling. By targeting distinct subgroups of the population, a population sample size can be reduced or optimized. This can provide cost, time and resource efficiencies.