California Mathematicians Develop Equation to Prevent Shootings
In an attempt to bring a scientific and data-driven approach to the debate surrounding gun control, two mathematicians from the University of California, Irvine have designed an equation based on statistical data that says reducing the availability of guns will reduce shooting deaths in America.
The husband-and-wife team, Dominik Wodarz and Natalia Komarova, used statistical data from existing studies on gun violence to create different measurements for their equation to predict what is the best method to prevent shootings. After plugging in numbers for different situations, the duo came to the conclusion that, at least for one-on-one shootings, gun control is the more beneficial option. Their findings were published on Friday in the journal PLOS ONE.
"We have now developed a scientific framework where we can argue about scientific data and assumptions, rather than having an emotional debate," Wodarz told U.S. News. "The framework has identified exactly what needs to be measured statistically in order to make these predictions."
Wodarz and Komarova evaluated factors such as the number of people who own guns, how many of those people carry a gun with them, and the likelihood that a person could avoid death by using a gun as defense. The team also looked at studies that evaluated the effect of reduced gun availability on the number of guns in the criminal population. Just as a navigation system in a car uses factors such as distance, speed limits and traffic conditions to find the optimal route between two points, the couple used these statistical measurements to devise the most ideal method to prevent firearm deaths.
http://www.usnews.com/news/articles/2013/07/26/california-mathematicians-develop-equation-to-prevent-shootings
Study Findings here: http://www.usnews.com/pubfiles/uc-irvine-gun-study.pdf
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...the new math I've heard about since 3rd grade. 
It has been argued that unrestricted gun availability promotes the occurrence of firearm-induced homicides. It has also been pointed out that gun possession can protect potential victims when attacked. This paper provides a first mathematical analysis of this tradeoff, with the goal to steer the debate towards arguing about assumptions, statistics, and scientific methods. The model is based on a set of clearly defined assumptions, which are supported by available statistical data, and is formulated axiomatically such that results do not depend on arbitrary mathematical expressions. According to this framework, two alternative scenarios can minimize the gun-related homicide rate: a ban of private firearms possession, or a policy allowing the general population to carry guns. Importantly, the model identifies the crucial parameters that determine which policy minimizes the death rate, and thus serves as a guide for the design of future epidemiological studies. The parameters that need to be measured include the fraction of offenders that illegally possess a gun, the degree of protection provided by gun ownership, and the fraction of the population who take up their right to own a gun and carry it when attacked.
I felt those sections of the abstract needed to be highlighted.