In stratified sampling, how is the population organized for sampling?

Stratified sampling is a method used to ensure that specific subgroups within a population are adequately represented in the sample. In this sampling technique, the population is divided into distinct categories or strata based on specific characteristics that are relevant to the study. This organization allows researchers to apply methods of analysis separately within each category, ensuring that differences within these groups can be explored and understood effectively.

For instance, if a researcher wants to study the opinions of various age groups on a new product, they might categorize the population into age strata (e.g., 18-24, 25-34, etc.). This division enables the researcher to compare results across these different strata, providing more nuanced insights that would be lost if the population were treated as a single unit. By applying different sampling methods or analyses to these categories, the researcher can enhance the reliability and validity of the results.

The other options do not accurately describe stratified sampling. Organizing the population as a single unit without categorization would overlook important differences, while random groups based solely on location wouldn't target specific characteristics of interest. Selecting individuals based only on age, without further categorization, also falls short of the structured approach that stratified sampling represents. Thus, structuring the population into specific categories for