What is a valid way to explore regional inequality using the Large Data Set?

• A. Compare indicators such as GDP per capita, life expectancy, or literacy across regions and discuss gaps.
• B. Use only national aggregates to assess inequality.
• C. Ignore regional differences and treat the country as uniform.
• D. Compare international indicators instead of regional ones.

Answer: (D)

Exploring regional inequality with the Large Data Set is about contrasting how different regions perform on common indicators to see the gaps that exist within a country. The dataset provides region-level values for measures such as GDP per capita, life expectancy, and literacy, so comparing these across regions lets you spot which areas are ahead and which are lagging, and by how much. This highlights inequality that national averages can hide and helps you discuss patterns, such as whether gaps are widening or narrowing over time or whether regional differences align with geography or urban-rural divides. Using regional comparisons (often with charts or maps) makes the analysis directly relevant to understanding domestic inequality. In contrast, relying only on national aggregates masks regional variation, ignoring how different parts of the country are faring, and focusing on international indicators shifts attention away from within-country disparities.