Skip to main content

Bayesian Approach to Intrepreting Archaeological Data

Bayesian Approach to Intrepreting Archaeological Data

Caitlin E. Buck, William G. Cavanagh, Cliff Litton

ISBN: 978-0-470-86608-5 October 2000 402 Pages





Statistics in Practice A new series of practical books outlining the use of statistical techniques in a wide range of application areas:
* Human and Biological Sciences
* Earth and Environmental Sciences
* Industry, Commerce and Finance
The authors of this important text explore the processes through which archaeologists analyse their data and how these can be made more rigorous and effective by sound statistical modelling. They assume relatively little previous statistical or mathematical knowledge. Introducing the idea underlying the Bayesian approach to the statistical analysis of data and their subsequent interpretation, the authors demonstrate the major advantage of this approach, i.e. that it allows the incorporation of relevant prior knowledge or beliefs into the analysis. By doing so it provides a logical and coherent way of updating beliefs from those held before observing the data to those held after taking the data into account. To illustrate the power and effectiveness of mathematical and statistical modelling within the Bayesian framework, a variety of real case studies are presented covering areas of common interest to archaeologists. These case studies cover applications in areas such as radiocarbon dating, spatial analysis, provenance studies and other dating methods. Background to these case studies is provided for those readers not so familiar with the subject. Thus, the book provides an examination of the theoretical and practical consequences of Bayesian analysis for examining problems in archaeology. Students of archaeology and related disciplines and professional archaeologists will find the book an informative and practical introduction to the subject.
The Bayesian Approach to Statistical Archaeology.

Outline of the Approach.

Modelling in Archaeology.

Quantifying Uncertainty: The Probability Concept.

Statistical Modelling.

Bivariate and Multivariate Distributions.

Bayesian Inference.

Implementation Issues.

Interpretation of Radiocarbon Results.

Spatial Analysis.

Sourcing and Provenancing.

Application to Other Dating Methods.

The Way Forward.