Raw numbers are easy to report and analyze, but without the proper context, they can be misleading. Is the effect you’re seeing real, or a simple result of the underlying, obvious distribution? Too many analyses and news stories end up reporting things we already know.
Data is often reported as a single number. Unemployment rates, housing prices, crime, etc. are all boiled down to single numbers that average over a large population. But averages, or means, hide much of the richness of the underlying data, and without at least a sense of the spread of the data values, are largely meaningless.