You would think that something so concrete, carefully recorded by authorities, wouldn’t be too tough to tabulate, even if at a large scale. Not so.
Homicide is a “serious crime that many people are concerned with, it is well-measured, and it is to a large degree well-reported and -recorded,” says Alfred Blumstein, a criminologist at Carnegie Mellon University. “That is not to say that there aren’t a variety of ways for fudging the measurement.”
Among the factors that cloud homicide numbers: gaps between police-reported numbers and counts by public-health organizations. The discrepancy is wide in many African countries and some Caribbean ones. The United Nations attributes the disparity to several factors, including definitional differences—whether honor killings should count—a lack of public-health infrastructure in some countries, and undercounting—possibly deliberate—by police.
I think this is something the common public often doesn’t understand about data. The numbers are entered and analyzed on a computer, so it’s easy to mistake data for mechanical output. It must be accurate, right? That’s usually not the case though, especially when it comes to data collection outside a controlled lab setting.
The game always changes when humans are involved. Not everyone responds to surveys, definitions of events vary across organizations, estimation methods change every year, and the list goes on.
For those who do stuff with data, you have to deal with that uncertainty, and as data consumers, you have to remember that numbers don’t automatically mean fact.