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Quantitative Analysis in Archaeology

As Todd VanPool and Robert Leonard note at the outset of their overall excellent treatment of the role of statistics in archaeology, very few of us enter the field because of a love of mathematics. Statistical analysis is nonetheless the most important and powerful tool available for archaeologists interested in constructing scientific explanations about past human behavior — an importance reflected in the undergraduate and graduate level statistics course requirements for students common at most universities. This book provides a detailed, highly accessible, and often witty presentation of both basic and more advanced statistical concepts and techniques. It would be an ideal text for an introductory archaeological statistics class — the “practice exercises” found at the end of each chapter certainly help the book fill that role. It also, however, can serve as a useful reference for practicing archaeologists. Arguably, the two most important words in any statistics book are “for example.” Fortunately, VanPool and Leonard have assembled interesting and highly relevant examples that help to make the sometimes complicated mathematics and the potentially intimidating formulas found throughout the book more accessible. They use hypothetical and actual archaeological data from a variety of geographic and temporal settings to illustrate how statistical methods can be used to help evaluate and explain common archaeological problems. Readers familiar with common types of archaeological data (e.g., ceramic and lithic morphometric data, site structure data, zooarchaeological data) should find the examples quite informative and useful. The organization of the book is similar to that of many statistics books. Following a brief introductory chapter outlining the purpose and goals of the book, Chapters two through six deal with the underlying basic terms and concepts of statistical analysis. Chapter two provides an easy to understand explanation of the difference in data measurement scales, and, importantly, detailed discussions and examples demonstrating the importance of recording and utilizing the correct measurement scale for a given question. As they do through much of the book, the authors point out common mistakes in how data are used in archaeological problem solving, giving novice students the means to not only design their own questions (and data collection) correctly but to also critically evaluate statistical arguments made by others. Chapters three and four present the most common visual and numerical methods of characterizing raw data, an important and sometimes overlooked first step in any problem oriented archaeological study. The importance of graph and table usage and design, a point that is often not made in introductory statistics texts, should prove to be quite useful to those unfamiliar with data representation. Likewise, the emphasis that the authors place on exploratory data analysis is a welcome approach. Given the wide availability of computer statistical packages (and, as the authors note in Chapter one, the tendency for some anthropological statistics classes to focus almost exclusively on computer program instruction), the temptation to immediately run data through automated complex statistical analysis techniques can be hard to resist. Unfortunately, without a basic understanding of the structure of the data and the evident patterning in the data, these more complex approaches can be misused, misleading, or flat-out wrong. Placing exploratory data analysis and data pattern recognition on par with hypothesis testing in archaeological analysis, as the authors do, is a strong point of the book. The concepts of probability and the normal distribution, the keys to understanding statistical inferences, are the focus of Chapters five and six. The standard simple event probability examples involving coins and dice (and a very relatable example involving the probability of finding an on-campus parking spot during the semester) are presented in a straightforward, easy to understand manner building a strong base for the more difficult issue of probability in complex events.