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The Monico Culture and Beyond Chronology, Using Bayesian Inference to Evaluate Hypotheses in Archaeology
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Description: EOC maintains this repository within the Open Science Framework to keep a DOI (DOI 10.17605/OSF.IO/54F62) and store the R Markdown, code, and data files necessary to replicate this manuscript, currently under review with Advances in Archaeological Practice. Here users may produce PDF and HTML versions of the manuscript for convenience. ABSTRACT Archaeologists frequently use probability and null hypothesis significance testing (NHST) statistics to assess how well survey, excavation, or experiment data align with their hypotheses about the past. Increasingly, archaeologists are adopting Bayesian statistics for this purpose. Many archaeologists are familiar with Bayesian statistics, mainly in radiocarbon date estimation and chronology building. However, Bayesian statistics have broader archaeological applications beyond chronology. The paper begins by briefly contrasting traditional and Bayesian statistical frameworks. Then, to walk readers through an example of Bayesian inference, the manuscript introduces the "Monico," a fictitious archaeological culture, and the "famous archaeologist," an academic authority on the Monico. The famous archaeologist has excavated a Monico archaeological site rich in material culture and composed of archaeofaunal remains. The manuscript then introduces Bayes' Theorem and guides the reader through an elementary step-by-step Bayesian analysis of the faunal remains as discrete data points to answer one of the famous archaeologist's research questions regarding the Monico dietary behavior. After the archaeologist answers their primary research question using Bayes' theorem, the manuscript transitions the reader from Bayesian analyses of discrete data points to analyses of data distributions. All in the context of evaluating archaeological hypotheses using zooarchaeological data recovered from multiple Monico sites. This part also guides the audience through a step-by-step "formal" example of how contemporary analysts apply Bayes' theorem to data distributions to evaluate scientific ideas in archaeology