Differentiate between raw data and aggregated data.

• A. Raw data are individual observations; aggregated data are grouped (by age, geography) for analysis and reporting.
• B. Raw data are averages; aggregated data are individual records.
• C. Raw data are qualitative; aggregated data are quantitative.
• D. Raw data are always more accurate than aggregated data.

Answer: (A)

Understanding the difference between raw data and aggregated data helps you see how information is used at different analysis levels. Raw data are the individual observations collected from each unit or event, keeping all the granular details. Aggregated data, on the other hand, are the summarized results that come from grouping those individual observations into categories (for example, by age group or geographic area) and then calculating simple summaries like counts or averages to reveal broader patterns.

This description matches the idea that raw data are individual observations and aggregated data are grouped for analysis and reporting, which is why this option is the best choice.

Notes on the other statements: raw data are not simply averages, nor are aggregated data simply individual records. The raw-versus-aggregated distinction isn’t about qualitative versus quantitative content, and raw data aren’t inherently more accurate than aggregated data—aggregation can reduce detail and noise, but it can also obscure variability.