Book Synopsis

Statistics in Practice A new series of practical books outliningthe use of statistical techniques in a wide range of applicationareas:

• Human and Biological Sciences
• Earth and Environmental Sciences
• Industry, Commerce and Finance

The authors of this important text explore the processes throughwhich archaeologists analyse their data and how these can be mademore rigorous and effective by sound statistical modelling. Theyassume relatively little previous statistical or mathematicalknowledge. Introducing the idea underlying the Bayesian approach tothe statistical analysis of data and their subsequentinterpretation, the authors demonstrate the major advantage of thisapproach, i.e. that it allows the incorporation of relevant priorknowledge or beliefs into the analysis. By doing so it provides alogical and coherent way of updating beliefs from those held beforeobserving the data to those held after taking the data intoaccount. To illustrate the power and effectiveness of mathematicaland statistical modelling within the Bayesian framework, a varietyof real case studies are presented covering areas of commoninterest to archaeologists. These case studies cover applicationsin areas such as radiocarbon dating, spatial analysis, provenancestudies and other dating methods. Background to these case studiesis provided for those readers not so familiar with the subject.Thus, the book provides an examination of the theoretical andpractical consequences of Bayesian analysis for examining problemsin archaeology. Students of archaeology and related disciplines andprofessional archaeologists will find the book an informative andpractical introduction to the subject.

From the Back Cover

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.

About the Author

Caitlin E. Buck is a British archaeologist and statistician specialising the application of Bayesian statistics to archaeology, and known for her work in radiocarbon dating. She is a professor in the Department of Mathematics and Statistics at the University of Sheffield.

William G. Cavanagh is the author of Bayesian Approach to Intrepreting Archaeological Data, published by Wiley.

Cliff D. Litton is the author of Bayesian Approach to Intrepreting Archaeological Data, published by Wiley.