In the decade since its publication, the first edition of Statistics for Archaeologists has become a staple in the classroom. Taking a jargon-free approach, this teaching tool introduces the basic principles of statistics to archaeologists. The author covers the necessary techniques for analyzing data collected in the field and laboratory as well as for evaluating the significance of the relationships between variables. In addition, chapters discuss the special concerns of working with samples. This well-illustrated guide features several practice problems making it an ideal text for students in archaeology and anthropology. Using feedback from students and teachers who have been using the first edition, as well as another ten years of personal experience with the text, the author has provided an updated and revised second edition with a number of important changes. New topics covered include: -Proportions and Densities -Error Ranges for Medians -Resampling Approaches -Residuals from Regression -Point Sampling -Multivariate Analysis -Similarity Measures -Multidimensional Scaling -Principal Components Analysis -Cluster Analysis Those already familiar with the clear and useful format of Statistics for Archaeologists will find this new edition a welcome update, and the new sections will make this seminal textbook an indispensible resource for a whole new group of students, professors, and practitioners.

This book is intended as an introduction to basic statistical principles and techniques for the archaeologist. It grows primarily from my experience in teaching courses in quantitative analysis for undergraduate and graduate stu dents in archaeology over a number of years. The book is set specifically in the context of archaeology, not because the issues dealt with are uniquely archaeological in nature, but because many people find it much easier to understand quantitative analysis in a familiar context-one in which they can readily understand the nature of the data and the utility of the tech niques. The principles and techniques, however, are all of much broader applicability. Physical anthropologists, cultural anthropologists, sociologists, psychologists, political scientists, and speCialists in other fields make use of these same principles and techniques. The particular mix of topics, the rela tive emphasis given them, and the exact approach taken here, however, do reflect my own view of what is most useful in the analysis of specifically archaeological data. It is impossible to fail to notice that many aspects of archaeological information are numerical and that archaeological analysis has an unavoid ably quantitative component. Standard statistical approaches are commonly applied in straightforward as well as unusual and ingenious ways to archae ological problems, and new approaches have been invented to cope with the speCial qUirks of archaeological analysis. The literature on quantitative analy sis in archaeology has grown to prodigious size in the past 25 or 30 years.

In the decade since its publication, the first edition of Statistics for Archaeologists has become a staple in the classroom. Taking a jargon-free approach, this teaching tool introduces the basic principles of statistics to archaeologists. The author covers the necessary techniques for analyzing data collected in the field and laboratory as well as for evaluating the significance of the relationships between variables. In addition, chapters discuss the special concerns of working with samples. This well-illustrated guide features several practice problems making it an ideal text for students in archaeology and anthropology. Using feedback from students and teachers who have been using the first edition, as well as another ten years of personal experience with the text, the author has provided an updated and revised second edition with a number of important changes. New topics covered include: -Proportions and Densities -Error Ranges for Medians -Resampling Approaches -Residuals from Regression -Point Sampling -Multivariate Analysis -Similarity Measures -Multidimensional Scaling -Principal Components Analysis -Cluster Analysis Those already familiar with the clear and useful format of Statistics for Archaeologists will find this new edition a welcome update, and the new sections will make this seminal textbook an indispensible resource for a whole new group of students, professors, and practitioners.

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.

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.

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

This fully revised second edition retains the hands-on simple approach of the first edition but with some significant modifications. Still covered in detail are descriptive and inferential techniques with each one worked through by hand on a common data-set, but new is a chapter covering an introduction to multivariate techniques. A new section provides SPSS PC programs designed with the beginner in mind. This book provides a practical manual to enable any archaeologist to start using statistics, as well as some more thoughtful considerations of the strengths and weaknesses of statistical methods and the results produced.

Quantitative Analysis in Archaeology introduces the application of quantitative methods in archaeology. It outlines conceptual and statistical principles, illustrates their application, and provides problem sets for practice. Discusses both methodological frameworks and quantitative methods of archaeological analysis Presents statistical material in a clear and straightforward manner ideal for students and professionals in the field Includes illustrative problem sets and practice exercises in each chapter that reinforce practical application of quantitative analysis

Statistics in Archaeology' presents the particular statistical methodologies which can be used to address specific issues and problems in archaeology. Through in-depth case studies, the author illustrates how such techniques can be employed in the archaeological context. These examples are taken from a wide range of different countries and reflect the international nature of archaeology, and its students and practitioners. The technical level of the book is intermediate and is for the academic and professional archaeologist needing to know more about the statistical techniques available to them. The structure and content of the book mean that it will also appeal to applied statisticians interested in how statistical methods can be used in different application areas.