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Dangerously Close to Big Data: The Intriguing Possibilities of Statistical Time Series Analysis in Archaeology and Paleoecology

Author(s): Elizabeth Scharf

Year: 2017

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Summary

Increasingly, archaeologists are producing larger databases and asking questions about processes that play out at larger scales. To better understand the working of long-term and regional-scale relationships, archaeologists are seeking to compare proxy variables measuring phenomena such as population, climate, and the environment. In this presentation, statistical time series in the time and frequency domains is used on sample datasets to illustrate the benefits of this approach in archaeology and paleoecology. For such applications, statistical time series analysis promises to reveal interactions, lead-lag relationships and statistically partition variability in ways that other approaches (such as visual inspection, regression, and correlations) cannot, providing insights into possible causal relationships and revealing subtle interactions that are otherwise hard to assess.


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Dangerously Close to Big Data: The Intriguing Possibilities of Statistical Time Series Analysis in Archaeology and Paleoecology. Elizabeth Scharf. Presented at The 81st Annual Meeting of the Society for American Archaeology, Vancouver, British Columbia. 2017 ( tDAR id: 429052)


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Abstract Id(s): 15914

Arizona State University The Andrew W. Mellon Foundation National Science Foundation National Endowment for the Humanities Society for American Archaeology Archaeological Institute of America