Chris Carleton

Complications in analytical archaeology

When asked what archaeology involves, few if any people answer math, statistics, and high-performance computing. Rather, people tend to think about dusty artifacts, long hours outside digging for evidence of forgotten civilizations, and Indiana Jones. In reality, archaeology can involve a lot of quantitative analysis. However, the proportion of quantitative analytical archaeologists is small compared to the field as a whole. And, while the quantitative database is increasing, the available quantitative methods for analyzing the data do not account for the peculiarities of the archaeological record. Consequently, many archaeological studies fall far short of explaining anything of interest about the past in a convincing way, despite a growing abundance of evidence amenable to rigorous analysis. To turn this situation around, I have begun developing quantitative analytical methods that are appropriate for archaeological data. Using a case study from my research, I will explain some of the analytical challenges archaeologists face. The case study involves a study of conflict in Classic Maya history from 300–900 CE. Using a time series model for count processes with a moving average, my co-authors and I found that there was a 530% increase in conflict levels for every degree increase in temperature over the study period. This finding has significant implications for understanding Classic Maya history and for current discussions about the impact of climate change on violent conflict. It also provided me several important insights into the challenges of quantitative analysis in archaeology. Hopefully, the insights I have gained so far and the tantalizing complexity of archaeological data will entice you to think about quantitative solutions, too.