I had some very unpleasant surprises when I was finally made it through the rigorous selection process and became a Marine Corps scout-sniper.  Along with the expected physical difficulty of the job came an even ruder awakening – we had to do math, and draw!  Long division, algebra and simple trig, without calculators, under field conditions, and while our partners were waiting for a firing solution.  Complicated scenarios could involve over a half-dozen calculations filling an entire page of notebook paper.  Most of us had not enlisted into the Marines to hone our math skills, and it had generally been years since we had worked formulas like this out.

Asking historians to do math is a lot like insisting that enlisted infantrymen use math, only you’re asking, not insisting.  There is usually a fundamental resistance to this kind of interdisciplinary integration because most historians 1) don’t like math, 2) aren’t good at math, 3) don’t really understand math and 4) were in competition in High School for the Biggest Nerd Award with the math geeks.  More seriously, though perhaps no more importantly, the use of numbers by historians implicates certain philosophical views of history.  Historians use numbers as a way to try and prove a point more completely.  If the historiography of history has a long link to the structuralist and objective nature of scientific thought, using numbers is a concrete way for historians to try (consciously or not) to get closer to those ideals.

I adhere to the idea that to a significant extent we can know history; a belief predicated on the belief that humans are not fundamentally protean, and that “human nature” exists and shows remarkable continuity (fascinatingly variable via external influences) through history.  Because of this viewpoint I find the judicious use of quantifiable data a helpful and valuable addition to historical research.  History often takes a tree or forest-level approach, looking at individuals or groups of individuals based upon the interpretation of subjective data.  The use of objective data can either give us different perspectives on that same level of data or it can allow us to examine entire forest regions – even ecosystems in a way that is not practical with other types of information.  This has been common practice in archaeology for quite some time, and it can be profitably applied to history.

There is however, a caveat, and that is that quantitative data usually needs to be subjected to statistical analysis (SA) to be valuable.  Without SA the analysis of data becomes as subjective an endeavor as the evaluation of notes and diaries – the significance becomes purely a subject of the researcher.  If the whole purpose of working with quantitative data is to access a more “accurate” and “scientific” approach then SA is vital to actually reaching that goal.  Unfortunately, teaching historians SA is like teaching Marines how to apply trig to marksmanship – if given the choice most would probably prefer to work off of instinct.  Until they see the results, that is!  Publishers should expect and demand that work that includes quantitative data, especially if the thesis is based around quantitative data be evaluated with accepted SA practices.  There are a bevy of computer programs available to take the pain out of the work; the biggest challenge is selecting a SA method and understanding how to apply the data to that method.  Crossing the hallway to the archaeology or even (*gasp*) the math department would probably make this a reasonably quick and painless experience.