Quantitative Archaeology in Roman Contexts. Some practical examples (original) (raw)
Notes on Quantitative Archaeology and R
This is a book-length treatment on the subject of statistical methods frequently used in Quantitative Archaeology and their implementation using the open-source software R. It is not intended as a textbook or as an introduction to either statistical methods or R, though it is intended to be accessible. There are plenty of good texts on these subjects to which this text might be seen as complementary. There is an emphasis on the analysis of real data sets, more so than in typical introductory quantitative archaeology texts. There is, similarly, an emphasis not to be found in other archaeological texts on the practicalities of implementation using modern statistical software, R. This is an open-source and extremely powerful package that has grown rapidly into something of an ‘industry-standard’ in applied statistics, and other application areas, that has not really touched archaeology much yet, at least in terms of what is visible in the literature. The underlying premise, that statistical methods are conceptually simpler, and more easily implemented, than is often conceded is spelled out in the introductory chapter. For those unfamiliar with R, and with data they need to analyse, one way of putting this is that there is life beyond Excel and SPSS well worth making the effort to discover. The text is moderately lengthy and is also available in the form of individual chapters, along with the data sets used, in Excel format.
Landmark papers in quantitative archaeology - a commentary
This paper is a modified version of part of the introduction to my 2003 book 'Statistics in Archaeology' that dealt with what I considered to be `landmark' papers in the development of quantitative archaeology up to to about 1990. The original text has largely been retained, but edited so that it reads coherently (I hope) as a paper in its own right. No changes have been made to the original selection, nor have new papers been added, but some of the entries have been expanded to include my later thoughts with reference to some later publications that have interested me. The section in the 2003 book on the journal and book literature has been retained, as it was, but with some additions.
Statistical Inference in Archaeology: Are We Confident?
Rethinking Israel: Studies in the History and Archaeology of Ancient Israel in Honor of Israel Finkelstein, 2017
We deal with the general issue of handling statistical data in archaeology for the purpose of deducing sound, justified conclusions. The employment of various quantitative and statistical methods in archaeological practice has existed from its beginning as a systematic discipline in the 19th century (Drower 1995). Since this early period, the focus of archaeological research has developed and shifted several times. The last phase in this process, especially common in recent decades, is the proliferation of collaboration with various branches of the exact and natural sciences. Many new avenues of inquiry have been inaugurated, and a wealth of information has become available to archaeologists. In our view, the plethora of newly obtained data requires a careful reexamination of existing statistical approaches and a restatement of the desired focus of some archaeological investigations. We are delighted to dedicate this article to Israel Finkelstein, our teacher, adviser, colleague, and friend, who is one of the father figures of this ongoing scientific revolution in archaeology (e.g., Finkelstein and Piasetzky 2010, Finkelstein et al. 2012, 2015), and wish him many more fruitful years of research.
The Use of Multivariate Statistics within Archaeobotany
Over the past several decades, use of multivariate statistics has become increasingly popular within archaeobotany. This paper outlines a brief history of the use of a variety of multivariate techniques, focusing on correspondence analysis and discriminant analysis, the two most popular techniques used today. Following a short description of the different techniques used, a survey of studies employing multivariate statistics is presented, highlighting the diversity of problems that can be addressed. Emphasis is given to studies of macrobotanical remains, particularly within the Old World, although studies of pollen, starch grains, and phytoliths, as well as those that integrate plant data with other types of archaeological data are also discussed.
Statistical tools in Landscape Archaeology
Archeologia e Calcolatori, 2010
Archaeological Predictive Models (APMs) represent an important evolution of spatial integrated databases of archaeological records. Before the development and the analysis of a predictive model, numerous other steps are required in order to integrate the raw data sets into functional archaeological systems. Our aim is to assess the evolution of archaeological data sets into APMs and to reconsider the real value of such attempts for the Romanian Heritage Protection or for scientific purposes. We will consider, as well, certain aspects regarding the deductive/inductive nature of the APMs. In our perspective, there are a few ways APMs could be improved: the use of more variables, as well as the understanding both of the analytical nature of data sets and of the real nature of archaeological data sets.
1992 - A systematic survey project in the Roman coastal area
Papers of the Fourth …, 1991
The systematic survey of Rome’s coastal zone, begun in 1988, has identified many new sites of all periods, ranging from the Palaeolithic to the Roman period. The project has sought to define a methodology of recording the archaeological data to provide more accurate analyses about territorial changes. The survey zone, the Malafede Valley , set on the immediate fringes of the city of Rome, has in fact suffered badly through urban expansion and the application here of a rigorous methodology has been of immense value. The considered factors comprise: 1. quantity and type of finds; 2. surface of each site; 3. climatic and environmental conditions; 4. morphological and pedological conditions affecting finds survival. The paper summarises the methods adopted in the Malafede survey and highlights the importance of excavation data to supplement the surface evidence.
1999
In the last years, the analysis of settlement patterns has been accomplished from different quantitative points of view, including statistic analysis, GIS, etc. This work is focused on obtaining a quantitative model of index parameters based in the UTM coordinates, using a 1:10.000 scale map. The set of indexes is studied by means of statistical analysis (Kruskal-Wallis, principal components analysis, cluster analysis and Voronoi tesselations), providing the chronocultural settlement patterns and the relationships between the archaeological site, the surrounding area and the chronological period of the site.