Spatial Data Analysis

This book gives an up-to-date overview of methodological and data-analytical issues of cross-cultural studies. Written by leading experts in the field, it presents the most important tools for doing cross-cultural research and outlines design considerations, methods, and analytical techniques that can improve ecological validity and help researchers to avoid pitfalls in cross-cultural psychology. By focusing on the relevant research questions that can be tackled with particular methods, it provides practical guidance on how to translate conceptual questions into decisions on study design and statistical techniques. Featuring examples from cognitive and educational assessment, personality, health, and intercultural communication and management, and illustrating key techniques in feature boxes, this concise and accessible guide is essential reading for researchers, graduate students, and professionals who work with culture-comparative data.

This collection explores the relevance of global trade law for data, big data and cross-border data flows. Contributing authors from different disciplines including law, economics and political science analyze developments at the World Trade Organization and in preferential trade venues by asking what future-oriented models for data governance are available and viable in the area of trade law and policy. The collection paints the broad picture of the interaction between digital technologies and trade regulation as well as provides in-depth analyses of critical to the data-driven economy issues, such as privacy and AI, and different countries' perspectives. This title is also available as Open Access on Cambridge Core.

This book gives an up-to-date overview of methodological and data-analytical issues of cross-cultural studies. Written by leading experts in the field, it presents the most important tools for doing cross-cultural research and outlines design considerations, methods, and analytical techniques that can improve ecological validity and help researchers to avoid pitfalls in cross-cultural psychology. By focusing on the relevant research questions that can be tackled with particular methods, it provides practical guidance on how to translate conceptual questions into decisions on study design and statistical techniques. Featuring examples from cognitive and educational assessment, personality, health, and intercultural communication and management, and illustrating key techniques in feature boxes, this concise and accessible guide is essential reading for researchers, graduate students, and professionals who work with culture-comparative data.

The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting.This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.

This textbook is a complete rewrite, and expansion of Hugh Rollinson's highly successful 1993 book Using Geochemical Data: Evaluation, Presentation, Interpretation. Rollinson and Pease's new book covers the explosion in geochemical thinking over the past three decades, as new instruments and techniques have come online. It provides a comprehensive overview of how modern geochemical data are used in the understanding of geological and petrological processes. It covers major element, trace element, and radiogenic and stable isotope geochemistry. It explains the potential of many geochemical techniques, provides examples of their application, and emphasizes how to interpret the resulting data. Additional topics covered include the critical statistical analysis of geochemical data, current geochemical techniques, effective display of geochemical data, and the application of data in problem solving and identifying petrogenetic processes within a geological context. It will be invaluable for

While some qualitative methods texts touch upon online communities as a potential data source, show how to conduct interviews and focus groups online, or select recording devices and analysis software

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To

Three books by the bestselling authors on Data Warehousing! The most authoritative guides from the inventor of the technique all for a value price.The Data Warehouse Toolkit, 3rd Edition (978111853080

Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method w

Basic Statistics with R: Reaching Decisions with Data, First Edition, provides readers with an understanding of the processes at work in using data for results. The work begins with data collection an

An examination of the datafication of family life--in particular, the construction of our children into data subjects. Our families are being turned into data, as the digital traces we leave are share

Downscaling is a widely used technique for translating information from large-scale climate models to the spatial and temporal scales needed to assess local and regional climate impacts, vulnerability, risk and resilience. This book is a comprehensive guide to the downscaling techniques used for climate data. A general introduction of the science of climate modeling is followed by a discussion of techniques, models and methodologies used for producing downscaled projections, and the advantages, disadvantages and uncertainties of each. The book provides detailed information on dynamic and statistical downscaling techniques in non-technical language, as well as recommendations for selecting suitable downscaled datasets for different applications. The use of downscaled climate data in national and international assessments is also discussed using global examples. This is a practical guide for graduate students and researchers working on climate impacts and adaptation, as well as for polic

The massive volume of data generated in modern applications can overwhelm our ability to conveniently transmit, store, and index it. For many scenarios, building a compact summary of a dataset that is vastly smaller enables flexibility and efficiency in a range of queries over the data, in exchange for some approximation. This comprehensive introduction to data summarization, aimed at practitioners and students, showcases the algorithms, their behavior, and the mathematical underpinnings of their operation. The coverage starts with simple sums and approximate counts, building to more advanced probabilistic structures such as the Bloom Filter, distinct value summaries, sketches, and quantile summaries. Summaries are described for specific types of data, such as geometric data, graphs, and vectors and matrices. The authors offer detailed descriptions of and pseudocode for key algorithms that have been incorporated in systems from companies such as Google, Apple, Microsoft, Netflix and T

Our experience of the world is influenced by numerous spatial biases, most of which influence us without our being aware of them. These biases are related to illusions and asymmetries in our perception of space, relationships between space and other qualities, dynamics of moving objects, dynamics of scene configuration, and dynamics related to perception and action. Consideration of these biases provides insight into how we perceive, remember, and navigate space, as well as how we interact with objects and people in space. This volume introduces and reviews numerous spatial biases, and provides descriptions and examples of each bias. The contributors discuss historical and current theories for many biases, and for some biases, provide new explanatory theories. Providing a 'one-stop shop' for information on such a key aspect of our experience in the world, this volume will interest anyone curious about our understanding of space.

How to use data as a tool for empowerment rather than oppression. Big data can be used for good--from tracking disease to exposing human rights violations--and for bad--implementing surveillance and c

In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply collaborative, deeply creative process behind 24 unique data visualization projects, spanning 12 different topics. The book provides

Categorical data requires a different methodology and techniques typically not encountered in introductory statistics courses. This title presents various ways of extracting real-life conclusions from

A manual celebrating the invention of architectural and spatial machines. It contains illustrated pieces which demonstrates the potential for spatial occupation, leading to new territories in architec

Provides yearly data on fatalities, refugees and internally displaced people for all major armed conflicts, alongside in-depth analysis of their political, military and humanitarian dimensions.

In Data Sketches, Nadieh Bremer and Shirley Wu document the deeply collaborative, deeply creative process behind 24 unique data visualization projects, spanning 12 different topics. The book provides

A primer for learning SAS and analytics quickly, the book makes use of real-world data analysis steps. Filled with line-by-line code explanations, it is packed with fully functional and easily modifia

A primer for learning SAS and analytics quickly, the book makes use of real-world data analysis steps. Filled with line-by-line code explanations, it is packed with fully functional and easily modifia

30-Second Data Scienceis the quickest way to discover how data is a driving force not just in the big issues, such as climate change and healthcare, but in our daily lives. Data science is an enti

Mathematicians have skills that would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics,

The authors of Big Data with Hadoop MapReduce: A Classroom Approach have framed the book to facilitate understanding big data and MapReduce by visualizing the basic terminologies and concepts. They em

The focus of this book is data analytics for COVID-19 which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platform

In Women, Gender and Conditional Cash Transfers, a multidisciplinary group of feminist scholars use survey data analysis, in-depth interviews, and ethnographic and archival research to explore the ext

In Women, Gender and Conditional Cash Transfers, a multidisciplinary group of feminist scholars use survey data analysis, in-depth interviews, and ethnographic and archival research to explore the ext

Data, Matter, Design presents a comprehensive overview of current design processes that rely on the input of data and use of computational design strategies, and their relationship to an array of

Data, Matter, Design presents a comprehensive overview of current design processes that rely on the input of data and use of computational design strategies, and their relationship to an array of

This book takes the reader through the basics of using the R statistical programming environment for data analysis using a series of case studies based around tasks that answer real research questions

This book takes the reader through the basics of using the R statistical programming environment for data analysis using a series of case studies based around tasks that answer real research questions

Understand both uncoded and coded caching techniques in future wireless network design. Expert authors present new techniques that will help you to improve backhaul, load minimization, deployment cost reduction, security, energy efficiency and the quality of the user experience. Covering topics from high-level architectures to specific requirement-oriented caching design and analysis, including big-data enabled caching, caching in cloud-assisted 5G networks, and security, this is an essential resource for academic researchers, postgraduate students and engineers working in wireless communications.

At the intersection between statistical physics and rigorous econometric analysis, this powerful new framework sheds light on how innovation and competition shape the growth and decline of companies and industries. Analyzing various sources of data including a unique micro level database which collects historic data on the sales of more than 3,000 firms and 50,000 products in 20 countries, the authors introduce and test a model of innovation and proportional growth, which relies on minimal assumptions and accounts for the empirically observed regularities. Through a combination of extensive stochastic simulations and statistical tests, the authors investigate to what extent their simple assumptions are falsified by empirically observable facts. Physicists looking for application of their mathematical and modelling skills to relevant economic problems as well as economists interested in the explorative analysis of extensive data sets and in a physics-orientated way of thinking will find

This fully revised fifth edition provides comprehensive coverage of flexible multibody system dynamics. Including an entirely new chapter on the integration of geometry, durability analysis, and design, it offers clear explanations of spatial kinematics, rigid body dynamics, and flexible body dynamics, and uniquely covers the basic formulations used by the industry for analysis, design, and performance evaluation. Included are methods for formulating dynamic equations, the floating frame of reference formulation used in small deformation analysis, and the absolute nodal coordinate formulation used in large deformation analysis, as well as coverage of industry durability investigations. Illustrated with a wealth of examples and practical applications throughout, it is the ideal text for single-semester graduate courses on multibody dynamics taken in departments of aerospace and mechanical engineering, and for researchers and practicing engineers working on a wide variety of flexible mul

Interpreting and applying macroeconomic analysis to the global economic environment and understanding the tools used to do so is fundamental to making good managerial decisions. Presuming no background in economic theory and prioritizing international application, this textbook introduces macroeconomics to business students. It explains how to understand domestic and global macroeconomic developments, policies, and data, and makes extensive use of case studies and data sets to present modern macroeconomics in a globalized world. Each chapter has several specific data exercises and practices as well as an international application focusing on the global perspective. By providing a host of international material, this book is useful for instructors and students around the globe.

Interpreting and applying macroeconomic analysis to the global economic environment and understanding the tools used to do so is fundamental to making good managerial decisions. Presuming no background in economic theory and prioritizing international application, this textbook introduces macroeconomics to business students. It explains how to understand domestic and global macroeconomic developments, policies, and data, and makes extensive use of case studies and data sets to present modern macroeconomics in a globalized world. Each chapter has several specific data exercises and practices as well as an international application focusing on the global perspective. By providing a host of international material, this book is useful for instructors and students around the globe.

Varieties of Democracy is the essential user's guide to The Varieties of Democracy project (V-Dem), one of the most ambitious data collection efforts in comparative politics. This global research collaboration sparked a dramatic change in how we study the nature, causes, and consequences of democracy. This book is ambitious in scope: more than a reference guide, it raises standards for causal inferences in democratization research and introduces new, measurable, concepts of democracy and many political institutions. Varieties of Democracy enables anyone interested in democracy - teachers, students, journalists, activists, researchers and others - to analyze V-Dem data in new and exciting ways. This book creates opportunities for V-Dem data to be used in education, research, news analysis, advocacy, policy work, and elsewhere. V-Dem is rapidly becoming the preferred source for democracy data.

This book offers a new interpretation of the spatial-political-environmental dynamics of water and irrigation in long-term histories of arid regions. It compares ancient Southwest Arabia (3500 BC–AD 600) with the American West (2000 BC–AD 1950) in global context to illustrate similarities and differences among environmental, cultural, political, and religious dynamics of water. It combines archaeological exploration and field studies of farming in Yemen with social theory and spatial technologies, including satellite imagery, Global Positioning System (GPS), and Geographic Information Systems (GIS) mapping. In both ancient Yemen and the American West, agricultural production focused not where rain-fed agriculture was possible, but in hyper-arid areas where massive state-constructed irrigation schemes politically and ideologically validated state sovereignty. While shaped by profound differences and contingencies, ancient Yemen and the American West are mutually informative in clarifyin

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic