Event Details

Carla Hadden is an Assistant Research Scientist in the Radiocarbon Dating Laboratory at the University of Georgia Center for Applied Isotope Studies. Dr. Hadden specializes in radiocarbon dating, environmental archaeology, and zooarchaeology, and is an Associate Editor for Radiocarbon, the main international journal of record for research articles relevant to radiocarbon techniques. She regularly publishes on radiocarbon method development and archaeological applications in high-impact journals such as Science Advances, American Antiquity, and Radiocarbon, and is regularly called upon to peer review manuscript submissions on radiocarbon dating and Bayesian chronological modeling in archaeology.

Bayesian chronological modeling revolutionized chronology building in archaeology. It provided a robust mathematical framework for incorporating all the dating information available, including radiocarbon dates, stratigraphy, artifact typologies, and the written historical record. The purpose of this seminar is to provide archaeologists with an introduction to the key concepts, assumptions, and terminology used in Bayesian chronological modeling; an overview of the basic structures and applications of age models; and an introduction to the “iterative approach” to sample selection and chronological modeling. We will introduce the audience to the several software options available for age modeling (OxCal, BCal, and various packages implemented in R) and compare their pros and cons. We will not provide a step-by-step “how to” for constructing models in any one program, but participants will receive a workbook and “quick start” guide for modeling in OxCal. This course will enable participants to understand and evaluate age models that they encounter in archaeological literature; will provide a necessary foundation for those interested in exploring how Bayesian models could contribute to their own projects; and will provide resources for those who wish to learn more about constructing chronological models. The intended audience includes those who have no previous experience in Bayesian chronological modeling.

1. Understand the basic terminology related to Bayesian chronological modeling, e.g., event; phase; sequence; boundary; MCMC; prior probability; posterior probability; likelihood; parameter; convergence; agreement
2. Evaluate and interpret model outputs
3. Understand and follow the conventions for reporting modeled dates in technical reports and scientific journals