Using Data to Find Likely Crime Spots

Posted to Statistics  |  Nathan Yau

I stumbled across this article about Aili Malm, a GIS specialist (I think) who uses social network analysis to find the most probably locations of organized crime.

"I look at where organized crime groups are located and I study how these groups are linked to one another," she explained. "I can chart their cell phone use or e-mail communication or with whom they co-offend. Based on these connections, I try to isolate the important players. Then I take the social and make it spatial. I look at individuals important to the criminal network and map where they live and where they commit their crimes."

It's just like that show Numb3rs on CBS. Albeit, math and statistics is a bit glorified on the show, but hey, at least it's loosely based on reality.


  • There are actually several papers about how social network analysis is being used to find OBL and how to explain the key players during 9/11.

    The biggest source of the exaggeration on Numb3rs involves small sample sizes.

  • oh for sure. I don’t doubt that there’s hundreds of papers about using statistics to find, understand, and fight crime. It’s always nice to see Stat in any kind of news form though :)


Years You Have Left to Live, Probably

The individual data points of life are much less predictable than the average. Here’s a simulation that shows you how much time is left on the clock.

Where Bars Outnumber Grocery Stores

A closer look at the age old question of where there are more bars than grocery stores, and vice versa.

Top Brewery Road Trip, Routed Algorithmically

There are a lot of great craft breweries in the United States, but there is only so much time. This is the computed best way to get to the top rated breweries and how to maximize the beer tasting experience. Every journey begins with a single sip.

Life expectancy changes

The data goes back to 1960 and up to the most current estimates for 2009. Each line represents a country.