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date: 12 December 2019

Abstract and Keywords

Statistics can be used to describe, model, and predict archaeological data, provided that the analyst has an understanding of the strengths and limitations of their data type and has a well-defined statistical population. This chapter discusses the major types of archaeological data, sampling strategies, and statistics appropriate for both describing and predicting outcomes for simple and complex ceramic datasets. Description and modeling of complex data can be done with many tools ranging from simple charts and histograms to more complicated methods, such as T-Test, Chi-Square Test, Multi-Response Permutation Procedure (MRPP), and Kernel Density Estimation (KDE), as well as Principle Components Analysis (PCA).

Keywords: data modeling, T-Test, Chi-Square Test, MRPP, KDE, PCA

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