What does stratified sampling involve?

Stratified sampling is a statistical method used to ensure that different segments of a population are adequately represented in a sample. In the context of investment and financial analysis, this method involves dividing an entire index or population into different sub-groups, or "strata," based on certain characteristics, such as industry sectors, market capitalizations, or geographical regions. Each of these strata is then sampled to ensure that every segment is represented proportionally in the overall sample.

This approach improves the efficiency and accuracy of conducting analyses, as it reduces sampling error and allows for a more comprehensive view of the total population. By sampling each "cell," or subgroup, in a structured manner, investors can gain insights that are more reflective of the entire index's behavior and characteristics.

Other options do not capture the essence of stratified sampling. While investing equal amounts across all sectors suggests a balanced approach, it does not involve sampling based on specific characteristics of the population. Sampling only high-return stocks implies a bias towards performance rather than ensuring representation across segments. Lastly, waiting for market corrections to sample does not relate to the systematic structure of stratified sampling, but rather responds to market timing, which is a different strategy altogether.