Mathematics And Archaeology

Although many archaeologists have a good understanding of the basics in computer science, statistics, geostatistics, modeling, and data mining, more literature is needed about the advanced analysis in these areas. This book aids archaeologists in learning more advanced tools and methods while also helping mathematicians, statisticians, and computer scientists with no previous knowledge of the field realize the potential of the methods in archaeological experiments.

This book is for students and practitioners of archaeology. It offers an introductory survey of all the applications of mathematical and statistical techniques to their work. These applications are increasingly concerned with computerized data classification and quantification, and their effect is to reduce the level of uncertainty in the interpretation of the evidence that time and chance have left. Any archaeologist wanting to find out what these new methods have to offer has hitherto been forced to search for information in the specialist handbooks, conference proceedings, and review articles of his own, and very often of other, disciplines. This book brings the information conveniently together, so far as it pertains to archaeology, and permits an assessment of its relevance and quality. Those who have been daunted by the specialist knowledge apparently demanded will now be able to acquire a thorough grasp of principles and practices. Only an elementary knowledge of mathematics is presumed throughout. Part 1 provides a brief introduction to basic concepts in archaeology and mathematics. Part 2 relates the standard archaeological techniques and procedures to mathematics; it concentrates on numerical approaches best suited to archaeological practices. Part 3 examines various automatic seriation techniques and discusses further work that is coming to play an essential part in the development of archaeology.

This book introduces archaeologists to the most important quantitative methods, from the initial description of archaeological data to techniques of multivariate analysis. These are presented in the context of familiar problems in archaeological practice, an approach designed to illustrate their relevance and to overcome the fear of mathematics from which archaeologists often suffer.

It is little secret that most archaeologists are uneasy with statistics. Thankfully, in the modern world, quantitative analysis has been made immensely easier by statistical software packages. Software now does virtually all our statistical calculations, removing a great burden for researchers. At the same time, since most statistical analysis now takes place through the pushing of buttons in software packages, new problems and dangers have emerged. How does one know which statistical test to use? How can one tell if certain data violate the assumptions of a particular statistical analysis? Rather than focusing on the mathematics of calculation, this concise handbook selects appropriate forms of analysis and explains the assumptions that underlie them. It deals with fundamental issues, such as what kinds of data are common in the field of archaeology and what are the goals of various forms of analysis. This accessible textbook lends a refreshing playfulness to an often-humorless subject and will be enjoyed by students and professionals alike.

Reveals the extent to which Foucault's approach to language in The Archaeology of Knowledge was influenced by the mathematical sciences, adopting a mode of thought indebted to thinkers in the scientific and epistemological traditions such as Cavailles and

Computer science—especially pattern recognition, signal processing and mathematical algorithms—can offer important information about archaeological finds, information that is otherwise undetectable by the human senses and traditional archaeological approaches. Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology offers state of the art research in computational pattern recognition and digital archaeometry. Computer science researchers in pattern recognition and machine intelligence will find innovative research methodologies combined to create novel and efficient computational systems, offering robust, exact, and reliable performance and results. Archaeologists, conservators, and historians will discover reliable automated methods for quickly reconstructing archaeological materials and benefit from the application of non-destructive, automated processing of archaeological finds.