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This graduate-level text aims to introduce students of the natural sciences to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own. A thoroughly updated and expanded version of the authors' successful textbook on geological factor analysis, this book draws on examples from botany, zoology, ecology, and oceanography, as well as geology. Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. The methods introduced in this book, such as classical principal components, principal component factor analysis, principal coordinate analysis, and correspondence analysis, can reduce masses of data to manageable and interpretable form. Q-mode and Q-R-mode methods are also presented. Special attention is given to methods of robust estimation and the identification of atypical and influential observations. Throughout the book, the emphasis is on application rather than theory.
Applied Factor Analysis was written to help others apply factor analysis throughout the sciences with the conviction that factor analysis is a calculus of the social sciences. The book developed from research undertaken to do a 236-variable cross-national analysis.
Geoinformatics is a component of Encyclopedia of Earth and Atmospheric Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Geoinformatics is a science which develops and uses information science infrastructure to address the problems of geosciences and related branches of engineering. The content of the theme on Geoinformatics is organized with state-of-the-art presentations covering the following aspects of the subject: Sample Data and Survey; Remote Sensing and Environmental Monitoring; Statistical Analysis in the Geosciences; International Cooperation for Data Acquisition and Use, which are then expanded into multiple subtopics, each as a chapter.. These two volumes are aimed at the following five major target audiences: University and College Students Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers and NGOs.
Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
Exploratory factor analysis (EFA) is a statistical tool for digging out hidden factors which give rise to the diversity of manifest objectives in psychology, medicine and other sciences. EFA had its heyday as psychologist Leon Thurstone (1935 and 1948) based EFA on what he called the “principle of simple structure” (SS). This principle, however, was erroneous from the beginning what remained unrecognized despite subsequent inventions of more sophisticated statistical tools such as confirmatory analysis and structural equation modeling. These methods are highly recommended today as tolerable routes to model complexities of observation. But they did not remove the harmful errors that SS had left behind. Five chapters in this book demonstrate and explain the trouble. In chapter 2 the ailment of SS is healed by introducing an unconventional factor rotation, called Varimin. Varimin gives variables of an analysis an optimal opportunity to manifest functional interrelations underlying correlational observations. Ten applications of Varimin (in chapter 2) show that its results are superior to results obtained by the conventional Varimax procedure. Further applications are presented for sports achievements (chapter 3), intelligence (chapter 4), and personality (chapter 5). If Varimin keeps on standing the tests new theoretical building blocks will arise together with conceptual networks promoting a better understanding of the domains under study. Readers may check this prognosis by themselves using the statistical tool (Varimin) which is provided by open access in the internet.
The third edition of Introduction to Environmental Forensics is a state-of-the-art reference for the practicing environmental forensics consultant, regulator, student, academic, and scientist, with topics including compound-specific isotope analysis (CSIA), advanced multivariate statistical techniques, surrogate approaches for contaminant source identification and age dating, dendroecology, hydrofracking, releases from underground storage tanks and piping, and contaminant-transport modeling for forensic applications. Recognized international forensic scientists were selected to author chapters in their specific areas of expertise and case studies are included to illustrate the application of these methods in actual environmental forensic investigations. This edition provides updates on advances in various techniques and introduces several new topics. - Provides a comprehensive review of all aspects of environmental forensics - Coverage ranges from emerging statistical methods to state-of-the-art analytical techniques, such as gas chromatography-combustion-isotope ratio mass spectrometry and polytopic vector analysis - Numerous examples and case studies are provided to illustrate the application of these forensic techniques in environmental investigations
Communication research is evolving and changing in a world of online journals, open-access, and new ways of obtaining data and conducting experiments via the Internet. Although there are generic encyclopedias describing basic social science research methodologies in general, until now there has been no comprehensive A-to-Z reference work exploring methods specific to communication and media studies. Our entries, authored by key figures in the field, focus on special considerations when applied specifically to communication research, accompanied by engaging examples from the literature of communication, journalism, and media studies. Entries cover every step of the research process, from the creative development of research topics and questions to literature reviews, selection of best methods (whether quantitative, qualitative, or mixed) for analyzing research results and publishing research findings, whether in traditional media or via new media outlets. In addition to expected entries covering the basics of theories and methods traditionally used in communication research, other entries discuss important trends influencing the future of that research, including contemporary practical issues students will face in communication professions, the influences of globalization on research, use of new recording technologies in fieldwork, and the challenges and opportunities related to studying online multi-media environments. Email, texting, cellphone video, and blogging are shown not only as topics of research but also as means of collecting and analyzing data. Still other entries delve into considerations of accountability, copyright, confidentiality, data ownership and security, privacy, and other aspects of conducting an ethical research program. Features: 652 signed entries are contained in an authoritative work spanning four volumes available in choice of electronic or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of communication research to more easily locate directly related entries. Back matter includes a Chronology of the development of the field of communication research; a Resource Guide to classic books, journals, and associations; a Glossary introducing the terminology of the field; and a detailed Index. Entries conclude with References/Further Readings and Cross-References to related entries to guide students further in their research journeys. The Index, Reader’s Guide themes, and Cross-References combine to provide robust search-and-browse in the e-version.
This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting the model to data. The author believes that the matrix-based learning of such models and objective functions is the fastest way to comprehend multivariate data analysis. The text is arranged so that readers can intuitively capture the purposes for which multivariate analysis procedures are utilized: plain explanations of the purposes with numerical examples precede mathematical descriptions in almost every chapter. This volume is appropriate for undergraduate students who already have studied introductory statistics. Graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis will also find the book useful, as it is based on modern matrix formulations with a special emphasis on singular value decomposition among theorems in matrix algebra. The book begins with an explanation of fundamental matrix operations and the matrix expressions of elementary statistics, followed by the introduction of popular multivariate procedures with advancing levels of matrix algebra chapter by chapter. This organization of the book allows readers without knowledge of matrices to deepen their understanding of multivariate data analysis.
Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring coverage on a broad range of topics such as data mining, portfolio optimization, and social network analysis, this book is ideally designed for business managers and practitioners, upper-level business students, and researchers seeking current research on large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques.
During the last 10 years numerical methods have begun to dominate paleontology. These methods now reach far beyond the fields of morphological and phylogenetic analyses to embrace biostratigraphy, paleobiogeography, and paleoecology. Paleontological Data Analysis explains the key numerical techniques in paleontology, and the methodologies employed in the software packages now available. Following an introduction to numerical methodologies in paleontology, and to univariate and multivariate techniques (including inferential testing), there follow chapters on morphometrics, phylogenetic analysis, paleobiogeography and paleoecology, time series analysis, and quantitative biostratigraphy Each chapter describes a range of techniques in detail, with worked examples, illustrations, and appropriate case histories Describes the purpose, type of data required, functionality, and implementation of each technique, together with notes of caution where appropriate The book and the accompanying PAST software package (see www.blackwellpublishing.com/hammer) are important investigative tools in a rapidly developing field characterized by many exciting new discoveries and innovative techniques An invaluable tool for all students and researchers involved in quantitative paleontology