Which of the following represents a key reason for stratifying a sample?

Stratifying a sample is a method used in data collection that involves dividing a population into distinct subgroups or strata to ensure that the sample accurately reflects the diversity within the population. The key reason for stratifying a sample is to achieve improved representation across diverse segments.

When researchers recognize that certain characteristics or factors are distributed unevenly in the population, stratification allows for more precise insights. By including proportional representation from each stratum, researchers can better understand the variations among different segments, leading to more reliable and valid conclusions. This becomes especially important when dealing with populations that have different demographics, behaviors, or attitudes, as it enhances the accuracy of the research findings.

In contrast, while economic efficiency and reduction in sample size may seem appealing, they do not capture the primary purpose of stratification, which is to enhance representation. Increased sample complexity, meanwhile, typically detracts from clarity in data analysis rather than serving as a main benefit of stratification. Overall, improved representation is what truly underpins the decision to stratify samples in marketing research.