Statistics of Deadly Quarrels

CarlNorthcore writes "Brian Hayes published this paper in the Computing Science chapter of Jan-Feb's American Scientist. It provides a fascinating and [sadly] relevant statistical exploration of our world's deadly conflicts. Look out for the excellent "Web of Wars" diagram."

Comments

Re:How To Stop Wars

[pmancini]

That is interesting. I am a big fan of Dunnigan. He is an impossible person to deal with in real life, so I hear, but he has a brilliant mind. His other related books make good reading as well. I especially liked his book on how the digital revolution has changed warfare over the years.

He and Keegan share a similar idea that is echoed in the article mentioned: "this respect, Richardson's data suggest that wars are like hurricanes or earthquakes: We can't know in advance when or where a specific event will strike, but we do know how many to expect in the long run. We can compute the number of victims; we just can't say who they'll be." Keegan in particular writes in "The Face of Battle" that war is very similar to natural disasters and lists the ways. A good read.

Finally, if one is interested in this sort of thing, Dunnigan and Austin Bay wrote "The Quick and Dirty Guide to Warfare" which makes predictions. The first book in the series was quite accurate 10 years later. The last update appears to be the 1996 third edition.

I didn't see anything about

[JeanBaptiste]

completely one sided wars, like Iraq v US (round 1)
wouldn't that be a high magnitude for Iraq and a low magnitude for the US?

and yes I do know that this study did not include that war... were there any completely one sided wars involved in the time frame studied?

Shouldn't this be scaled to the population?

[rebill]

One comment at the end of the article caught my attention:

We now have it in our power to have a magnitude-8 or -9 war. In the aftermath of such an event, no one would say that war is demographically irrelevant. After a war of magnitude 9.8, no one would say anything at all.

This points out a comparison problem within the original research - it does not take into account the population increases over time. For example, somewhere in the mid-1600s, London had a population of 600,000 people, while it currently has a population near 7,000,000. That is the difference between a magnitude-5.7 and a magnitude-6.8 event, using the given scale.

Would factoring in the population growth curve enhance or reduce the apparent randomness of the data?

Napoleon's march into Russia

[jcsehak]

There's a cool map of Nappy's march into Russia, which shows, visually, the losses suffered by the thickness of the line, among other things. Really beautifully rendered. Edward Tutfe (master of information design) is a big fan of it, understandably so.