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.
Grant S. McCall is the Executive Director of the Center for Human-Environmental Research and Associate Professor of Anthropology at Tulane University. He is also the author of Before Modern Humans: New Perspectives on the African Stone Age and (with Karl Widerquist) Prehistoric Myths in Modern Political Philosophy.
List of Figures
List of Tables
List of Boxes
List of Formula
Chapter 1: Introduction: How Does Quantitative Analysis Fit Into Archaeological Research?
Chapter 2: Basics: Knowing Your Data
Chapter 3: Preparing Your Data: Aggregation, Standardization, and Transformation
Chapter 4: Numerical and Graphical Approaches to Summarizing Your Data
Chapter 5: Basic Approaches for Statistical Hypothesis Testing Using Univariate Data
Chapter 6: Bivariate Analysis: Linear Regression and Correlation
Chapter 7: Multivariate Techniques for Data Reduction and Pattern Recognition
Chapter 8: Multivariate Approaches to Statistical Hypothesis Testing
Chapter 9: Clustering and Discrimination: Grouping Data According to Similarity
Chapter 10: Conclusion: Numerical Facts in the World of Archaeological Ambiguity