What is the purpose of dividing a population into strata in stratified random sampling?

Dividing a population into strata in stratified random sampling serves the primary purpose of achieving a more balanced representation in each strata group. This method involves segmenting the population into distinct subgroups, or strata, based on specific characteristics such as age, gender, income level, or any other relevant criterion. By ensuring that each stratum is adequately represented in the sample, researchers can capture the diversity and variations within the population, leading to more accurate and reliable results.

This technique helps to increase the efficiency and precision of estimates when analyzing the data, as it allows for comparisons between different subgroups within the population. As a result, findings are more likely to reflect the true nature of the population being studied, rather than being skewed by over- or under-representation of certain groups.