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"The use of archaeological remote sensing applications to address academic and applied research problems is growing at a tremendous rate in North America. Fueling this growth are new research approaches using innovative instrumentation technologies and data collection methods. Increasingly, researchers pursuing these new approaches are integrating remote sensing data collection with theory-based interpretations to address anthropological questions within larger research programs. This work is a must-have, up-to-date volume for today's archaeologists. The book includes numerous applications of remote sensing in North American contexts that exemplify the methodological developments and increase of theory-based archaeological remote sensing interpretation and presentation theoretical developments that have occurred since 2006. It covers the major remote sensing methods and their integration with relevant technologies such as geographic information systems (GIS) and GPS. Targeted to practitioners of archaeological remote sensing as well as students, this suite of current and exemplary applications adheres to high standards for methodology, processing, presentation, and interpretation"--Provided by publisher.

Indians of North America --- Archaeology --- Antiquities --- Remote sensing. --- Research. --- United States

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This book takes a unique approach to explaining permutation statistics by integrating permutation statistical methods with a wide range of classical statistical methods and associated R programs. It opens by comparing and contrasting two models of statistical inference: the classical population model espoused by J. Neyman and E.S. Pearson and the permutation model first introduced by R.A. Fisher and E.J.G. Pitman. Numerous comparisons of permutation and classical statistical methods are presented, supplemented with a variety of R scripts for ease of computation. The text follows the general outline of an introductory textbook in statistics with chapters on central tendency and variability, one-sample tests, two-sample tests, matched-pairs tests, completely-randomized analysis of variance, randomized-blocks analysis of variance, simple linear regression and correlation, and the analysis of goodness of fit and contingency. Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity, depend only on the observed data, and do not require random sampling. The methods are relatively new in that it took modern computing power to make them available to those working in mainstream research. Designed for an audience with a limited statistical background, the book can easily serve as a textbook for undergraduate or graduate courses in statistics, psychology, economics, political science or biology. No statistical training beyond a first course in statistics is required, but some knowledge of, or some interest in, the R programming language is assumed.

Statistical science --- Biomathematics. Biometry. Biostatistics --- biomathematica --- biostatistiek --- statistiek --- biometrie --- statistisch onderzoek